Error control schemes for networks: An overview - Binghamtonnael/classes/cs528/error-control.pdf · Mobile Networks and Applications 2 (1997) 167–182 167 Error control schemes for

Mobile Networks and Applications 2 (1997) 167–182 167

Error control schemes for networks: An overview

Hang Liu a, Hairuo Ma a, Magda El Zarki a and Sanjay Gupta b

a Department of Electrical Engineering, University of Pennsylvania, 200 S. 33rd Street, Philadelphia, PA 19104, USAb Motorola, GSM Products Division, 1501 West Shure Drive (IL27-3205), Arlington Heights, IL 60004, USA

In this paper, we investigate the issue of error control in wireless communication networks. We review the alternative error controlschemes available for providing reliable end-to-end communication in wireless environments. Through case studies, the performanceand tradeoffs of these schemes are shown. Based on the application environments and QoS requirements, the design issues of errorcontrol are discussed to achieve the best solution.

1. Introduction

In recent years there has been an increasing trendtowards personal computers and workstations becomingportable. Desire to maintain connectivity of these portablecomputers to the existing installation of Local Area Net-works (LANs), Metropolitan Area Networks (MANs), andWide Area Networks (WANs), in a manner analogous topresent day computers, is fueling an already growing inter-est in wireless networks. Wireless networks will be neededto provide voice, video and data communication capabilitybetween mobile terminals and also to permit such termi-nals to have access to wireline networks. However, beforewireless networks can be employed for packet voice, video,data, and other applications, it is important that appropriatecommunication protocols suited for the wireless environ-ment are developed. Of specific interest are “physical”,“link” and “network” layer protocols that take into accountthe characteristics of the underlying communication chan-nel.

Wireless channels provide error rates that are typicallyaround 10−2. Such high error rates result due to multipathfading which characterize mobile radio channels. However,many applications such as video and data transmissions re-quire that the error rates be significantly smaller. In additionto the poor channel quality, the design of wireless commu-nication systems is complicated by the rapidly changingquality of the radio channel.

To increase the apparent quality of a communicationchannel there exist the following two distinct approaches:

• Forward Error Correction (FEC) which employs errorcorrecting codes to combat bit errors (due to channelimperfections) by adding redundancy (henceforth paritybits) to information packets before they are transmitted.This redundancy is used by the receiver to detect andcorrect errors.

• Automatic Repeat Request (ARQ) wherein only errordetection capability is provided and no attempt to cor-rect any packets received in error is made; instead it is

requested that the packets received in error be retrans-mitted.

FEC and ARQ are two basic categories of error con-trol techniques. ARQ is simple and achieves reasonablethroughput levels if the error rates are not very large.However, in its simplest form, ARQ leads to variable de-lays which are not acceptable for real-time services. FECschemes maintain constant throughput and have boundedtime delay. However, the post decoding error rate rapidlyincreases with increasing channel error rate. In order toobtain high system reliability, a variety of error patternsmust be corrected. This means that a powerful long codeis necessary, which makes the coder-decoder pair hard toimplement and also imposes a high transmission overhead.Further complicating matters is that the wireless channelis non-stationary, and the channel bit error rate varies overtime. Typical FEC schemes are stationary and must be im-plemented to guarantee a certain Quality Of Service (QOS)requirement for the worst case channel characteristics. Asa consequence, FEC techniques are associated with unnec-essary overhead that reduces throughput when the channelis relatively error free.

In order to overcome their individual drawbacks, thecombination of these two basic classes of error controlschemes, called hybrid ARQ schemes, have been devel-oped [12,13,31,32].

Specifically, this paper examines the alternatives avail-able for providing a reliable end-to-end communicationchannel in wireless networks and discusses their impacton network design and protocols. The paper is organizedas follows: In sections 2 and 3, the two fundamental tech-niques for error detection and correction, FEC and ARQare reviewed, respectively. In section 4 we discuss hybriderror control techniques, i.e., schemes that combine FECand ARQ in their efforts to construct a reliable pipe fordata transfer. In section 5, we present case studies and ex-amples from existing and future networks that highlight themerits and demerits of the above error control methods anddiscuss the relevance of each for various practical applica-tions. Finally, the discussion is summarized in section 6.

Baltzer Science Publishers BV

168 H. Liu et al. / Error control schemes for networks

2. Forward error correction

Forward error correction involves addition of redundantbits (henceforth referred to as parity bits), that are used toaid in correcting any bits that are received in error. Shan-non’s channel coding theorem [8] states that there alwaysexists a coding scheme that enables information to be trans-mitted over any given channel with arbitrarily small errorprobabilities provided the data rate (including that due toparity bits) over the channel is less than the channel capac-ity (as defined by the classical Shannon’s theorem). Overthe last four decades a number of powerful and efficientcodes have been designed [8,16,19,23].

2.1. Block coding

Block coding schemes divide a bit stream into non-overlapping blocks and code each block independently.Block codes used in practical applications today belongto the class of linear cyclic codes, since these codes lendthemselves to easier implementations. A coding scheme isreferred to as being linear if the sum of two code vectors isalso a code vector. Similarly, a coding scheme is referred toas being cyclic if all cyclic shifts of a code vector results in avalid code vector. Binary Bose–Chaudhuri–Hocquenghem(BCH) codes and non-binary Reed–Solomon (RS) codesare two kinds of widely used linear cyclic block codes.

2.1.1. Bose–Chaudhuri–Hocquenghem (BCH) codesFor any positive integers, m > 3 and t < 2m−1, there is

a binary BCH code with the following parameters, (referredto as an (n, k, t) BCH code):

• block length: n = 2m − 1,• number of parity check bits: n− k 6 mt,• minimum distance: dmin > 2t+ 1.

Each binary BCH code (n, k, t) can correct up to t-bit er-rors, and thus it is also referred to as a t-error-correctingcode.

2.1.2. Reed–Solomon (RS) codesThe binary BCH codes can be generalized to non-binary

codes. If p is a prime number and q is any power of p,there exist BCH codes with q-ary symbols. For any choiceof positive integer s and t, a q-ary BCH code is of lengthn = qs−1, which is capable of correcting any combinationof t or fewer symbol errors and requires no more than 2stparity-check symbols. RS codes are a subclass of non-binary BCH codes with s = 1. A (n, k, t) RS code withq-ary symbols has the following parameters:

• block length: n = q − 1,• number of parity-check bits: n− k = 2t,• minimum distance: dmin = 2t+ 1.

An (n, k, t) RS code is capable of correcting any combina-tion of t or fewer symbol errors. In practical applications,RS codes with code symbols from q = 2m are chosen.

BCH and RS block coding schemes have a well definedalgebraic structure, which has facilitated the developmentof efficient coding and decoding schemes. In addition, RScodes have optimal “distance properties”, i.e., provide op-timal error correction capability given a fixed number ofparity bits, and excellent “burst error suppression” capabil-ities.

2.2. Code shortening

Often, a block code of desirable natural length or suitablenumber of information digits may not exist. In this case,code shortening is performed, which involves choosing acode with block length greater than the required length andsubsequently shortening it to meet the requirement. Codeshortening is most easily done by setting a selected numberof the information symbols to zero in the encoding opera-tion. For example, given an (n, k) code C, consider the setof code vectors for which the b leading high-order infor-mation symbols are equal to zero. Such code vectors forma subset of code C. If the b zero information symbols aredeleted from each of these code vectors, we obtain a set ofvectors of length n − b. These shortened vectors form an(n−b, k−b) code. The error detection and correction capa-bility of the shortened code is at least as great as the codefrom which it was derived. For RS codes, the minimumdistance is unchanged after shortening.

2.3. Convolutional codes

Block coding schemes are frequently referred to as mem-oryless since successive information blocks are coded in-dependently. Convolutional codes are a popular class ofcoders with memory, i.e., the coding of an informationblock is a function of the previous blocks. An (n, k,m) con-volutional code generates n encoded bits for every k infor-mation bits, where m refers to the memory of the encoder.The n encoder outputs at any given time instant, depend notonly on the k inputs but also on m previous input blocks(where (m+ 1) is sometimes referred to as the code con-straint length) [16]. Figure 1 shows a rate 1/2 binary con-volutional encoder withm = 4. For each input bit, there are2 output bits which depend on the previous 4 input bits. Theencoder consists of an m-stage shift register together withn modulo-2 adders and a multiplexer for serializing the en-coder outputs. If the input sequence is u = (u0,u1,u2, . . .),the two encoder output sequences v(1) = (v(1)

0 , v(1)1 , v(1)

2 , . . .)and v(2) = (v(2)

0 , v(2)1 , v(2)

2 , . . .) are equal to the convolutionof the input sequence u with the two code generator se-quences g(1) = (1, 0, 0, 1, 1) and g(2) = (1, 1, 1, 0, 1), i.e.,the encoding equations are v(1) = u∗g(1) and v(2) = u∗g(2).

In general, for convolutional codes, each information se-quence (input, output or code generator sequence) can bewritten as a polynomial with the coefficients of the poly-nomial being equal to the elements of the correspondingsequence. In this case the output polynomial is equal to

H. Liu et al. / Error control schemes for networks 169

Figure 1. Rate 1/2 convolutional encoder with m = 4.

the product of the input polynomial and generator polyno-mial. For the (2, 1, 4) convolutional code discussed above,the encoding equations are

V (i)(D) = U (D)G(i)(D), i = 1, 2, (1)

where

U (D) = u0 + u1D + u2D2 + · · · ,

V (1)(D) = v(1)0 + v(1)

1 D + v(1)2 D2 + · · · ,

V (2)(D) = v(2)0 + v(2)

1 D + v(2)2 D2 + · · · ,

and

G(1)(D) = 1 +D +D4,

G(2)(D) = 1 +D2 +D3 +D4

are referred to as the generator polynomials of the code.After multiplexing, the code vector is

V (D) = V (1)(D2)

+DV (2)(D2).

Encoding for both linear cyclic block codes and linearconvolutional codes involves simple arithmetic operationsand therefore they are easily implemented. If a block codeis used for error detection, only simple integer division isneeded; however, decoding block codes or convolutionalcodes for error correction is much more tedious. For blockcodes, an iterative algorithm is often used to correct theerrors. Error correction algorithms become quite complexfor long codes with large error correction capability; es-pecially, for non-binary codes. For convolutional codes,decoders are often based on the Viterbi algorithm whichis known to be an optimal algorithm [16]. Its decodingcomplexity grows exponentially with code memory length.Therefore it is effective for short memory length codes.Many other decoding algorithms such sequential decoding,majority-logic decoding, etc. have also been developed;interested readers are referred to [8,19] for a more detaileddiscussion.

2.4. Code puncturing

The characteristics of a wireless channel typically varywith time, and therefore to obtain optimal performance itis necessary to adapt the error coding scheme to the chang-ing channel characteristics. Code puncturing allows an en-coder/decoder pair to change code rates, i.e., code error

correction capabilities, without changing their basic struc-ture [11–13]. Code puncturing involves not transmitting(i.e., deleting) certain code bits. It is important to note thatboth convolutional codes and block codes can be punctured.

Punctured convolutional codes were first introduced byClark et al. [9]. Hagenauer modified the concept of punc-tured convolutional codes for the generation of a familyof rate compatible punctured convolutional (RCPC) codesby adding a rate-compatibility restriction to the puncturingrule [12]. The rate-compatibility restriction implies that allthe code bits of a high rate code of the family are used bythe lower rate codes. These codes are attracting more andmore attention because of their flexibility.

We now discuss in some detail the process of puncturingcodes. A low rate 1/n convolutional code (called mothercode) is periodically punctured with period p to obtain afamily of codes with rate p/v, where v can be varied be-tween p + 1 and np. As an example, we consider punc-tured convolutional codes obtained from a rate 1/3 mothercode. To generate a rate p/v punctured convolutional code(p/v > 1/3), we delete (3p− v) bits from every 3p codebits corresponding to the encoded output of p informationbits by the original rate 1/3 code. The resulting rate isthen equal to the desired rate r = p/v. The puncturedcodes have the same number of states as the mother code,i.e., the same memory length m. The deleted bit patternmust be carefully chosen to obtain desirable performance.

We now illustrate code puncturing with the help of anexample. Consider the rate 1/3 mother code defined bythe generator polynomials: G(1) = D4 + D + 1, G(2) =D4 +D3 +D2 + 1 and G(3) = D4 +D2 +D+ 1. Its punc-turing matrices with a puncturing period of 8 are given intable 1 [12]. Each matrix has 8 columns and 3 rows, cor-responding to the puncturing cycle and the branches at theoutput of the rate 1/3 coder, respectively. The elementsof puncturing matrices are only zeros and ones. A zero ina puncturing matrix means that the corresponding code bitwill not be transmitted, a one means that it is inserted inthe channel bit stream. For example, to generate a 8/22code, puncturing matrix p(8/22) is used. Encoding of 8information bits with the three generator polynomials re-sults in 3×8 intermediate bits at the three output branches.Every fourth and eighth output bit of the third branch isdeleted. Instead of transmitting 3 × 8 bits, only 22 bitsare transmitted per 8 information bits. Therefore, a rate8/22 code is generated. In general, the puncturing matrixp(r = p/v) = [pij] for a mother code of rate 1/n and apuncturing period of p has n rows and p columns. Thenumber of zeros in the puncturing table is equal to np− v.

Two punctured convolutional codes, obtained from thesame mother code, are said to be rate-compatible if all thecode bits in the higher rate code are used in the lower ratecodes. Let p(r1) and p(r2) be the puncturing matrices of tworate-compatible codes (p/p+1 > r1 > r2). If an element inp(r1) is equal to one (pij(r1) = 1), then the same element inp(r2) is also equal to one (pij(r2) = 1). Given a high-ratepunctured convolutional code with puncturing matrix p(r1),


Table 1Puncturing table for RCPC codes with mother code rate 1/3, memory m = 4 and period p = 8.

Code 8/9 8/10 8/12 8/14 8/16 8/18 8/20 8/22 8/24rate r

Punctur- 1111 0111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111ing 1000 1000 1000 1000 1010 1010 1110 1110 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111matrix 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 1000 1000 1100 1100 1110 1110 1111 1111

a lower rate-compatible punctured convolutional code canbe generated if we replace some zeros of p(r1) with onesand retain the previous ones in p(r1). For example, if wereplace the fifth zero of the first row in the puncturingmatrix of a rate 8/9 code (p(8/9) given in table 1) witha one, the puncturing matrix of a rate 8/10 compatible codewill be obtained.

The encoder for a punctured code can be fabricated us-ing the original low-rate convolutional encoder followedby a bit selector which deletes specific code bits accordingto a given puncturing rule. Only the bit selection rule ischanged to generate different rates of codes. At the receiverside, a Viterbi decoder based on the mother code decoderis used for decoding the punctured codes of the family. Todecode different rate codes, only metrics are changed ac-cording to the same puncturing rule used by the encoder(the deleted bits are not counted when calculating the pathmetrics). RCPC codes have been shown to offer nearlyequivalent performance when compared with the best pre-viously known codes of the same rate. However, they aremuch simpler to decode than conventional convolutionalcodes.

2.5. Code selection

Having discussed various coding schemes, we now con-sider criteria that must be taken into account when selectinga FEC scheme for any given application.

1. Probability of uncorrected errors: Since it is impos-sible for any coding scheme to detect all errors andcorrect them, it is important to choose coding schemesfor which the probability of both undetectable and un-correctable (but detectable) errors is minimized (or sat-isfies the application under consideration).

2. Overhead: The FEC codes should add as little as pos-sible overhead and maximize the code rate. However,increased code capability generally leads to lower coderate.

3. Complexity: The implementation complexity of thecoding/decoding scheme which typically increases withincrease in code length and its capability to detect andcorrect errors.

Before proceeding further we present some numericalresults and illustrate the impact FEC has on various per-formance characteristics. Let’s first consider the impact ofusing binary BCH codes on a channel that is characterizedby random errors.

Figure 2. BER performance of BCH codes over random error channels.

Figure 2 shows the decoding performance versus aver-age channel SNR for BCH(127, 120, 1), BCH(127, 106,3), BCH(127, 92, 5), and BCH(127, 78, 7) codes. Theassociated overheads are 5.5%, 16.5%, 27.5%, and 38.5%,respectively. As expected, increased code error correctioncapability reduces decoding error rate but requires moreredundancy.

For any given code rate (ratio of parity bits and blocksize) the error correction capability of a block codingscheme increases with increase in block size. Therefore,a larger block size enables one to utilize the channel moreefficiently. Larger block codes also help mitigate the effectof burst errors, that often characterize wireless channels.However, the use of larger block sizes creates several prob-lems. First, the packetization delay1 increases with increasein block size, and this limits the maximum block size thatcan be used in various applications. Second, the implemen-tation complexity of a coding system grows exponentiallywith increase in the block length for block codes or withmemory length for convolutional codes, limiting codewordlengths.

Considerable effort has been directed towards imple-menting long, powerful codes with minimal complexity.Cascading of two or more codes was proposed as a meansof constructing long codes which could be encoded and de-coded in a simple manner [8,14,16,19]. A simple concate-nated code is formed from two codes in series. The codecloser to the channel is called the inner code, whereas thecode outside the inner code is known as the outer code. Fig-

1 The time required to collect data bits to form a block of desired size.


Figure 3. Block diagram of communication system using a concatenated code.

Figure 4. Structure of product codes [28, figure 4.71, p. 479].

ure 3 shows the diagram of a concatenated coding systemthat employs two interleavers. (Interleavers are described indetail in the next subsection.) The inner interleaver random-izes bursty channel errors. The outer interleaver is used be-cause the errors resulting from the inner decoder are burstyin nature. The other method to form a long code whilestill maintaining coder-decoder simplicity is to use a prod-uct code [16,28]. Typically, product codes are obtained byencoding the information symbols in two dimensions; k1k2

information symbols are arranged in a matrix with k1 rowsand k2 columns. Each row is encoded by an (n2, k2, t2)code and each column is encoded by an (n1, k1, t1) code.Then the information matrix with the dimensions (k1× k2)is encoded to the dimension of (n1 × n2). Figure 4 showsan example of a product code by using RS(15, 11, 2) codefor the rows and the shortened RS(6, 4, 1) for the columnswhere the symbol size is 4 bits for both the codes [28].

The performance of a specific code depends on the cod-ing rate, the code length, the modulation schemes, the chan-nel error patterns, etc. It is difficult to choose the best codefor all the different channel conditions and system require-ments. Figure 5 gives a general comparison for several dif-ferent coding schemes over Rayleigh fading channels withMSK modulation:

(1) RS(57, 29, 14) code with a symbol size of 8 bits andno interleaving (the block size is 456 bits),

(2) RS(12, 6, 3) with a symbol size of 4 bits and blocksymbol interleaving over 9 codewords (the block sizeis 432 bits),

(3) (2, 1, 4) convolutional codes with bit interleaving (theblock size is 448 bits) [28].

All the coding schemes here have a code rate about 1/2.The BER performance curves of the two RS codes have across-over at a channel SNR of 21 dB. Below 21 dB, theshorter RS(12, 6, 3) code is better than the longer RS(57,29, 14) code. The longer code having a larger symbol field,suffers a higher channel symbol error rate that is likely tocause more decoding errors. This results in a worse perfor-mance. Above 21 dB, the longer RS(57, 29, 14) code yieldsa better performance than the shorter RS(12, 6, 3) code be-cause it has more parity symbols in a codeword and betterburst-dispersing properties, that is, a higher correcting ca-pability, The convolutional code results in a BER perfor-mance better than both RS codes. This can be contributedto using soft-decision Viterbi decoding which makes use ofthe channel information.

Figure 6 compares the performance of concatenated andproduct codes [28]. The product code uses a RS(15, 11, 2)code and a RS(6, 4, 1) code with a symbol size of 4 bits.Two concatenated coding schemes are considered:

(1) RS(48, 36, 6) with an 8-bit symbol as the outer codeand a rate 2/3 convolutional code obtained by punc-turing a (3, 1, 4) mother code as the inner code,

(2) RS(48, 36, 6) with an 8-bit symbol as the outer codeand a rate 2/3 convolutional code obtained by puctur-ing a (3, 1, 6) mother code as the inner code.

The performance of the product code is poor because thecodes used for both dimensions are very weak (double errorcorrecting code for the rows and single error correctingcodes for the columns). About 0.5 dB gain can be obtainedwhen the mother code memory length increases from 4 to6 for the two concatenated coding schemes.


Figure 5. BER performance of different codes over Rayleigh fading channel [28, figure 4.72, p. 481].

Figure 6. BER performance of concatenated and product codes over Rayleigh fading channel [28, figure 4.73, p. 481].

2.6. Interleaving

An alternative to choosing long codes to combat the ef-fect of burst errors is interleaving. Interleaving simply in-volves interleaving symbols from two or more codewordsbefore transmission on the channel. The number of code-words that are interleaved is referred to as the depth of theinterleaver, m. Figure 7 shows a interleaver with a inter-leaving depth of m and a codeword length of N . The datais written row-by-row into a m × N matrix and read outcolumn-by-column by the interleaver before sending it overthe channel. The reverse process is performed at the dein-terleaver. Therefore, between successive symbols of anygiven codeword there are m − 1 symbols that belong tothe m− 1 other codewords being interleaved. If the inter-leaver has sufficient depth the fading processes that affectsuccessive symbols belonging to the same codeword willbe uncorrelated. Therefore, from the perspective of anysingle codeword, interleaving makes a burst error channelappear as one which has only random errors. Note that

Figure 7. Interleaver.

interleaving does not decrease the long-term bit error ratebut it is successful in decreasing the number of errors ineach codeword, therefore the codeword should have enoughcapability to correct the erroneous symbols in it after dein-terleaving.

Results in [34] show that the FEC and interleaving strat-egy is effective when tm exceeds 1/r where t is the code er-ror correction capability and 1/r is the average burst length.


Note that interleaving results in extra delay because dein-terleaving can be started only after all the interleaved datais received. For the above example, a delay on the orderof 1/rt codewords is introduced.

3. Automatic Repeat Request (ARQ)

ARQ is an error control mechanism that relies on re-transmitting data that is received with errors [20]. In suchschemes, messages are divided into blocks of suitable size,that are transmitted after a small number of parity bits havebeen added. At the receiver these parity bits are used todetect the presence of errors in the received packet. Incase errors are detected in a received packet, the receiverrequests a retransmission of the packet.

Automatic Repeat Request (ARQ) protocols roughly op-erate as follows: The transmitter numbers the packets to betransmitted sequentially (using numbers from a finite set)and maintains a timer for each packet it transmits. The re-ceiver acknowledges, at the very least, the receipt of eachsuccessful packet (a packet that is received with no errors)by transmitting a packet, referred to as an ACK bearingthe sequence number of the packet being acknowledged.Packets that have not been successfully acknowledged, i.e.,an ACK has not been received, in a predetermined timeinterval, henceforth referred to as timeout, are assumed tobe lost (or corrupted) and are retransmitted.

In some cases, negative acknowledgements (NAKs) aretransmitted by the receiver for every packet received inerror. If NAKs are employed, a packet is retransmitted fol-lowing the receipt of a negative acknowledgement. Sincesome of the transmitted packets can be lost or misrouted,NAKs can not be transmitted for these lost packets. Wenow briefly describe three of the most popular ARQ proto-cols – Stop and Wait, Selective Repeat, and Go-Back-N.

3.1. Stop and Wait

When using the Stop and Wait (SW) ARQ protocol, theDLC protocol transmits a packet only when all previouslytransmitted packets have been successfully acknowledged.Hence, when using SW, the transmitter after transmitting apacket waits for its acknowledgement. Once its acknowl-edgement has been received the next packet is transmitted.However, if an acknowledgement does not arrive until atimeout timer expires, the packet is retransmitted. There-fore, in SW there is never more than a single packet thatis unacknowledged at any given instant of time. Since thetransmitter does not use the available channel during timeintervals it waits for an ACK, the maximum data trans-fer rate that can be supported is limited. This limits caseswhere the SW ARQ protocol can be employed.

3.2. Selective Repeat

Unlike SW, when using Selective Repeat (SR), packets,if available, are transmitted continuously by the DLC layer.

As before, the receiver acknowledges each successfully re-ceived packet by transmitting an ACK bearing the sequencenumber of the packet being acknowledged. If an acknowl-edgement is not received for a packet before the expirationof the timeout, the packet is retransmitted. Once a packethas been retransmitted the transmitter resumes transmis-sion of packets from where it left off, i.e., if a is the packetwith the largest sequence number that has been transmitted,packet with sequence number a+ 1 is transmitted next (as-suming that no other timers have expired in the meantime).Since when the SR ARQ protocol is employed, packets arecontinuously being transmitted the inefficiency associatedwith SW is eliminated. Observe that when SR is employedpackets can be accepted out of sequence. Hence, packetsreceived out of sequence have to be buffered and sequencedbefore they can be delivered.

3.3. Go-Back-N

When Go-Back-N (GBN) is employed, packets aretransmitted continuously as in SR. However, at the receiver,the DLC layer accepts packets only in the order in whichthey were transmitted. Packets received out of sequenceare discarded and not acknowledged. Since the receiveraccepts packets only in-sequence, after a timeout, the trans-mitter retransmits the packet that timed out and all packetswith sequence numbers that follow the one that was re-transmitted. Hence, each time a timeout occurs all packetsthat are yet to be acknowledged are retransmitted. It isimportant to observe that GBN attempts to combine the de-sirable features of SR and SW, i.e., packets are transmittedcontinuously, as in SR, without the need to buffer out ofsequence packets and there is no resequencing overhead.

4. Hybrid error control

Given that neither FEC nor ARQ alone can deliver thedesired performance it is necessary that hybrid ARQ errorcontrol schemes (that use both FEC and ARQ) be used.There are two types of hybrid ARQ schemes, type-I andtype-II. Type-I hybrid ARQ includes parity bits for botherror detection and error correction in every transmittedpacket, using either a single code designed for simultaneouserror correction and detection or a correction code as theinner code along with a detection code as the outer code.If the number of erroneous symbols in a received code-word is within the error correction capability of the code,the errors are corrected. If an uncorrectable error patternis detected, the receiver discards the received codewordand requests a retransmission. The transmitter retransmitsthe same codeword. When the retransmitted codeword isreceived, the decoder again attempts to correct the errorswithin the error-correction capability of the code. If thepacket arrives with detectable but uncorrectable errors aretransmission is requested again. This process continuesuntil the codeword is successfully accepted or the maximumallowed retransmission attempts have been exhausted.


On the other hand, in type-II hybrid error controlschemes any codewords that could not be successfully de-coded are saved, while simultaneously requesting for aretransmission. In case it is not possible to successfullydecode the retransmitted codeword, the saved (corrupted)codewords are used to aid in the decoding process. (Notethat it is not necessary that the same codeword be retrans-mitted.) The above process is repeated if the codeword canstill not be successfully decoded. We refer the reader to[12,16] for an in-depth discussion of hybrid error controlschemes.

For hybrid error control schemes to be effective it is im-perative that an optimal mix of FEC and ARQ to be usedbe determined. The design of hybrid error control schemesis critically dependent on the application being supported asdifferent applications place vastly varying demands on thenetwork. For example, for data transfer, maximum achiev-able throughput is a key performance measure. On theother hand for packet voice it must be ensured that theend-to-end packet loss probability is below a prespecifiedthreshold and that the tail of the end-to-end packet delaydistribution is bounded [21].

For example, let us consider a type-I hybrid ARQscheme with a block size of n with k information digits, anderror correction capability t. We would like to determinethe optimal error correction capability, t∗, that should beemployed to achieve maximum throughput given an ARQprotocol and FEC coding scheme. The throughput dependson the coding scheme (n, k, t), ARQ protocol, and the chan-nel error probability p. Figure 8 shows the throughput as afunction of the error correction capability for various ARQand FEC schemes. Evaluating closed form expressions forthe optimal error correction capability is difficult. How-ever, the asymptotic results can be obtained. For any ARQprotocol, if the product of code length and the channel er-ror rate np is large the optimal error correction capability(for BCH or RS codes) and the maximum throughput are,respectively,

t∗ ∼ np+ O(√np)

and (2)

Λ(p,n, t∗

)∼ C(1− cp) + o(1), (3)

c is a constant that depends on the FEC coding schemebeing employed. For binary BCH codes c = m and forReed–Solomon codes c = 2. Further, it can be shown that

ΛSR(p,n, t) ∼

0, if t < np− εnp,1− cp+ o(1), if |np− t| < εnp,1− ct/n, if np+ εnp < t.

The above asymptotic results indicate that if the np is largeand if the error correction capability, t of the FEC schemeused is smaller than np, minimal throughput is obtained. Ift is larger than np, the achievable throughput decreases lin-early with increase in t. This “threshold” nature of the func-tion Λ(p,n, t) can be easily seen (with threshold t/np = 1)in figure 8. As expected, the threshold effect is more pro-nounced as np increases.

The asymptotic results are explained intuitively as fol-lows. Valuable transmission capacity is wasted if the FECis either too weak or too strong. For optimal operation,the amount of FEC needed for each codeword should beexactly equal to the number of errors in the received code-word. However, since errors occur randomly ideal opera-tion cannot be achieved. An approach to achieve close toideal operation would involve choosing the error correctioncapability of np, the expected number of errors in a code-word of size n which is transmitted over a channel witherror probability p. As the codeword size increases the co-variance (covariance of a random variable is defined as theratio of the variance of the random variable to the squareof its mean) in the number of errors in any given codeworddecreases. This implies, that the FEC ability provided foreach codeword, is more often that not, just enough to cor-rect the errors. This means that close to ideal operation canbe obtained as the codeword size increases for any giventransmission channel.

We now discuss the implication of the asymptotic resultson the design of hybrid error recovery schemes. From theasymptotic results discussed above it follows that a suitablydesigned error coding scheme can help utilize most of theavailable channel capacity. However, to achieve the upperbound it is necessary that a sufficiently large codeword sizeshould be chosen. Furthermore, from (2) and figure 8 itcan be concluded that to maximize throughput the choiceof error correction capability should be conservative, andshould always exceed the threshold. Note that the penalty(due to loss in throughput) for choosing t below the optimalis substantially higher than when t exceeds the optimal. Itshould also be noted that the asymptotically optimal errorcorrection capability does not depend on the ARQ protocol.A look at figure 8 indicates that the difference between t∗GBNand t∗SR is marginal (also note that t∗GBN − t∗SR decreaseswith increasing np). Therefore, in a hybrid error controlscheme the FEC and the ARQ protocols could be designedindependently.

The above observations were made on the basis of theassumption that the objective is to maximize throughput.We must however caution that network protocols (otherthan error control) and applications often pose conflictingdesign choices. Some of the factors that govern the choiceof the codeword size are: (i) packetization delay, (ii) storeand forward delay at intermediate nodes, and (iii) the over-head due to packet headers.

ARQ schemes are used for data transmission since dataapplications require error free transmission. FEC codesare generally employed as an error control mechanism inreal-time applications because they maintain a constant andbounded time delay. Long deep fades cause extremelybursty channel errors. An adaptive error control schemesuch as a hybrid ARQ scheme may be well suited for thiskind of fluctuating channel.

Original hybrid ARQ schemes, proposed for data trans-mission, impose unacceptable delays for real-time services.The concept of error control coding with a limited number


Figure 8. The throughput for the hybrid ARQ scheme using different FEC codes.

of retransmissions is proposed in [20] in order to bounddelays (truncated hybrid ARQ). Note that for delay con-strained real-time data, the transmitted packets become use-less if they do not reach their destination before a prede-termined time. Therefore, in truncated hybrid ARQ, thetransmitter just drops packets that have not been correctlydelivered once their deadline has expired.

5. Case studies

We now present examples from existing and future wire-less networks to illustrate the concepts that have been out-lined previously. The case studies presented highlight themerits and demerits of various error control methods anddiscuss the relevance of each for various practical applica-tions. However, before we proceed it is important to reviewthe basic factors that need to be considered when designing

optimal error control schemes for various wireless network-ing applications.

• Wireless channel characteristics: There is no univer-sal error control scheme that is optimal for all kinds ofchannels because of the diversity of wireless channels.An investigation and modeling of the channel character-istics is the first step in the design of an error controlscheme.

• Service requirements: Different kinds of services havedifferent QoS requirements which impose different re-quirements on error control, such as BER and delay.

• Adaptation and graceful degradation: Wireless chan-nels are time-varying. An effective error control schemeshould be capable of adapting to the channel conditions.When the channel conditions are good, less error protec-tion is needed, so that more information can be trans-mitted. When the channel conditions are poor, more


protection needs to be added. An error control schemeshould also consider the quality requirements of sources.Different error protection capabilities are provided to thedata based on its importance to the overall quality and itsresilience to errors. For example, an ATM cell headerneeds more protection. So do the I-frames in MPEGvideo sequences.

• Complexity and availability of off-the-shelf technolo-gies.

5.1. Narrow band systems

The second generation cellular systems are based ondigital technology. These systems are currently being de-ployed. These systems are designed to support low bitrateservices using circuit-switched time division multiple ac-cess (TDMA) or code division multiple access (CDMA).

5.1.1. Global System for Mobile Communications (GSM)The Pan-European GSM System uses TDMA (Time Di-

vision Multiple Access) with eight timeslots per radio chan-nel [22,28]. Each user transmits periodically in a slot.The slot duration is approximately 0.58 ms which leadsto a TDMA frame duration of approximately 4.6 ms. Theinformation is transmitted in bursts at a rate of approxi-mately 271 kbit/s using Gaussian Minimum Shift Keying(GMSK) modulation over a bandwidth of 200 kHz. GSMsupports two types of traffic channels: a full rate trafficchannel, which carries channel encoded information at arate of 22.8 kbit/s, and half rate traffic channel at a rate of11.4 kbit/s. A full rate traffic channel occupies one timeslot.For the half-rate traffic, two connections are mapped ontothe same timeslot, transmitting data in alternating frames.

Here we only discuss the error control used in the fullrate traffic channel. The interested reader can find moredetails in [22,28]. For full rate speech transmission, thespeech coder delivers 260 bits every 20 ms at a bit rate of13 kbit/s. The first 50 significant speech bits are encodedusing a (53, 50) error detecting block code with the genera-tor polynomial G(D) = D3 +D+1. The coded 53 bits andthe next 132 bits are reordered. 4 tail bits are then addedfor terminating the convolutional encoder memory. These189 bits are encoded by a (2, 1, 4) convolutional encoderto give 378 bits. The code uses the generator polynomialG(1) = 1 + D3 + D4 and G(2) = 1 + D + D3 + D4. Theleast significant 78 bits are left unprotected. This resultsin a total frame length of 456 bits, which corresponds to abitrate of 22.8 kbit/s.

This frame is then divided into eight 57-bit sub-blocks.The sub-blocks are block diagonally interleaved and theninterburst interleaved, resulting in 114-bit bursts that consistof two sub-blocks. A 114-bit burst is transmitted in a timeslot with some control information.

User data transmission is also supported at a rate of9.6 kbit/s, 4.8 kbit/s or 2.4 kbit/s on a full rate traffic chan-nel and at a rate of 4.8 kbit/s or 2.4 kbit/s on a half ratetraffic channel. The same half-rate convolutional code used

Figure 9. Structure of IS-95 frame.

for speech is used but with longer interleaving intervals.A higher layer protocol such as TCP can be employed togurantee error free delivery using retransmissions.

5.1.2. CDMA based digital cellular networks (IS-95)The EIA/TIA IS-95 standard is based on CDMA [22,

29,30]. The forward (base-to-mobile) and reverse (mobile-to-base) links use different channel coding and spreadingprocess. For simplicity, of the many data rates supported,we discuss the case of 9.6 kbit/s traffic channels (with aframe period of 20 msec). Each frame contains 172 infor-mation bits, 12 CRC bits as frame quality indicator, and8 tail bits for terminating convolutional encoder memory.Figure 9 shows the frame structure. Before interleaving andspreading, the forward links use a rate 1/2 convolutionalcode with the generator functions

G(1)(D) = 1 +D +D2 +D3 +D5 +D7 +D8

and

G(2)(D) = 1 +D2 +D3 +D4 +D8.

On the reverse traffic channels, the data is encoded using arate 1/3 convolutional code with the generator functions

G(1)(D) = 1 +D2 +D3 +D5 +D6 +D7 +D8,

G(2)(D) = 1 +D1 +D3 +D4 +D7 +D8

and

G(3)(D) = 1 +D1 +D2 +D5 +D8

prior to interleaving and spreading.Data services are also offered over IS-95 cellular net-

works. The standard is refered as IS-99 [30]. In the IS-95standard, the physical layer frame can carry either primarytraffic only, or multiplexed primary and secondary traffic.Voice is considered to be primary traffic and user data canbe either primary or secondary, determined at call setuptime. The error control for data traffic employs two levelsof recovery. The lower level recovery protocol, called theradio link protocol (RLP), accomplishes partial error recov-ery between the mobile and the base station. RLP is basedon a NAK-ed ARQ scheme and that allows a maximum oftwo retransmissions. If the data burst is still in error aftertwo retransmissions, the recovery is left up to the higherlayer such as TCP/IP/SNDCF/PPP, to guarantee error freedelivery.


Figure 10. A recommended error control architecture for application of FEC, interleaving, and data link ARQ to provide wireless ATM servicess [33,figure 9].

5.2. Wireless ATM networks

ATM is designed to be a transmission and networkinginfrastructure for high speed multimedia services (video,voice, data, and others). With the desire to provide ubiq-uitous access and the acceptance of ATM as a standard forbroadband networking applicable to both synchronous andasynchronous services, wireless ATM has been receivingincreased attention over the past 2–3 years [1,4,25–27].

ATM is designed for very low error rate and bandwidth-rich media, but wireless channels are time-varying and errorprone with limited bandwidth. So, effective and robust datalink layer control schemes (error control and flow control)are necessary to support ATM over wireless channels. Be-low we briefly introduce some of the error control schemesproposed in the recent literature on wireless ATM services.

In [7], an error control architecture is recommended toavoid performance degradation when using ATM over wire-less links. The principal components of the proposed ar-chitecture and the functions are as follows:

• Channel interleaving to randomize burst errors amongdifferent cells.

• FEC to reduce channel error rate. The Reed–Solomon/Viterbi concatenated code is used, it is a very powerfulFEC code with reasonable complexity using currentlyavailable VLSI decoder chips.

• ATM interleaving to randomize the error bursts out ofthe FEC decoder within one cell. The cell headers (fivebytes each) are interleaved with the data stream so thatno more than a single error from a burst error appearsin any cell header. Recall that in ATM the cell headeris capable of correcting a single bit error.

• Data Link ARQ to provide reliable transmission forapplications that require reliable delivery. Data linkprotocol parameters can be determined in a straightfor-ward manner given the channel characteristics. The Go-Back-N protocol may be used on relatively good chan-nels, whereas Selective Repeat protocol is preferred overseverely impaired channels.

In [15], a method for reducing the cell loss probability byinterleaving the header and the payload bits over a wirelessATM link is introduced. There exist two distinct methodsfor performing interleaving in an ATM environment:

Figure 11. One method of cell unit interleaving method [15, figure 1].

• interleaving headers of multiple cells (block unit inter-leaving), and

• spreading each bit of a header over the payload fieldwithin the cell (cell unit interleaving).

The block unit interleaving method is very effective forburst errors of length up to the number of bits equal tothe number of cells in one block unit. This incurs a largeprocessing delay for interleaving. The cell unit interleav-ing distributes all of the 40 header bits of a cell at 10 bitintervals across the cell. The method is effective for bursterrors shorter than 11 bits by transforming burst errors intorandomly distributed single-bit errors which can be easilycorrected by the ATM header. Even if long bit errors occur,the burst errors will not affect other cells because the inter-leaving is done within a single cell. Cell unit interleavingalso incurs a shorter processing delay. Simulation resultsverified that the cell unit interleaving scheme reduces cellloss probability effectively and is easily applicable to PDH,SDH and cell-based physical layers. It is also more robustthan block unit interleaving against unexpected long bursterrors.

A straightforward approach to evolve from ATM to wire-less ATM is to use a standard ATM cell for network levelfunctions, while a wireless header-tailer is added on theradio link for wireless channel specific protocol layers –MAC (Medium Access Control), DLC (Data Link Control)and the network control layer [33]. DLC layer is used toprovide increased error protection. Service class specific re-transmission strategies are used to improve error recoverywith a minimal decrease in the wireless channel utilization.


Figure 12. CBR DLC: Operation of FIFO and transssfer of cells to the ATM layer [33, figure 4].

Figure 13. ATM cell and coded cell format [2, figure 2].

For ABR (available bit rate) services, DLC uses the tradi-tional ARQ procedure as there are no delay bounds. ForCBR (constant bit rate) and VBR (variable bit rate), sourceretransmissions are bounded to a limit specified by the ap-plication at VC (virtual connection) setup time. For the

Figure 14. Optimal quality for 1- and 2-layer schemes (Flower Garden)[6, figure 7].

CBR service, to maintain a constant bit rate channel, theretransmissions need to use additional bandwidth so as notto impair the throughput of the CBR connection.

ATM employs Header Error Correction (HEC) to pro-tect the ATM cell header from single-bit errors. However,wireless ATM requires a more powerful scheme to improveBER performance. In [2], a new FEC scheme is proposedthat modifies the cell structure of ATM cells to improveerror correction ability. Two different FEC codes, one forthe header, which is a powerful coding gain code, and theother for the payload, which is a higher coding rate code,are adopted. The coded cell is modified into a wirelessATM cell in which the HEC is discarded and two FECsare added. After replacing the HEC in the ATM cells withthe FECs, the wireless ATM cells are transmitted. Aftererror correction at the receiver, the FECs are discarded anda new HEC is generated to regenerate the original ATMcell stream.


Figure 15. The average PSNR of the reconstructed video sequence under different error control schemes [17, figure 4].

One major service class supported by ATM constitutesvideo-related services which usually require high through-put, low bit error rate and are delay sensitive. Becauseof the time-varying property of the wireless link, layeredvideo source coding and unequal error protection schemeshave received great attention in recent years.

Layered coding and unequal error protection schemesraise two questions. One is how to code the source infor-mation into different priority layers, and the other is howto choose appropriate error protection for different prioritylayers. An FEC-based error control scheme in combinationwith 2-layer video coding techniques is used to transportthe MPEG-2 video over an indoor broadband ad hoc wire-less ATM LAN is proposed in [5]. Two models for theindoor TDMA wireless channel are presented. One is therandom loss model, where the wireless channel is character-ized by uncorrelated bit errors introduced by random noiseand interference components. The other is the multipathloss model, where the transmitted signal undergoes impair-ment due to multipath fading, shadowing and co-channelinterference. Most wireless channels can be modeled bya combination of these two models. Error control on thewireless link is achieved by means of a channel encoder–decoder. RS encoding–decoding was chosen because itleads to minimal overhead and the commercial availabil-ity of 80 Mb/s encoders–decoders. The FEC-based schemeincludes three possible levels [3]:

• Bit-level FEC: This is done at the physical layer, typi-cally in hardware, by means of a DSP chip or a specificIC. For a bandwidth limited channel, trellis coded mod-ulation with Viterbi decoding is used. If the channel isnot band limited, block or convolutional encoding areemployed.

• Byte-level FEC: This is done on a per-packet basis. Tra-ditionally, every packet carries a CRC field for errordetection only. Recently, because of more powerfulprocessing abilities, use of this field for error correc-tion is also possible. The authors adopted the Reed–Solomon(RS) encoder to process symbols where a sym-bol is a group of m bits. The RS encoder processesN data symbols to generate 2t symbols, where t is thenumber of symbols that can be corrected by a RS en-coder.

• Cell-level FEC: This is done by allocating some re-dundant cells for error correction. In the case of cellsthat cannot be corrected by bit-level or byte-level FEC,the redundant cells, together with the correctly receivedcells, are used to recover the lost cells without retrans-missions. For instance, the cell sequence numbers areused to detect the location of lost cells. k RS symbols arethen sufficient to recover from k errored symbols. Thus,up to s lost cells can be recovered by the s redundantcells using a RS codec or another maximum distance


Figure 16. The throughputs of the system under the different error control schemes [17, figure 5].

separable code. An alternative to cell-level coding is touse per-cell coding with interleaving at the cost of delaydue to interleaving.

In order to achieve best possible video quality over wire-less ATM, scalable or layered source coding is necessary.Several 2-layer coding techniques have been investigatedin the literature [5].

• Data Partitioning (DP), which divides encoded DCT co-efficients into two groups: low frequency componentsinto a base layer with high priority (HP) and high fre-quency components into an enhancement layer with lowpriority (LP).

• SNR Scalability (SNRS), which first uses a coarse quan-tizer to encode the DCT coefficients to create a baselayer with high priority (HP) and then uses a fine quan-tizer on the errors to create an enhancement layer withlow priority (LP).

Simulation results based on the error characteristics ofeach model showed that byte-level coding was appropriatefor random losses while cell-level coding provides protec-tion against multipath channel losses. For both random andmultipath channel models, 2-layer scalable MPEG-2 out-performs 1-layer MPEG-2, and 2-layer coding using SNRScalability outperforms Data Partitioning at a cost of com-plexity [6].

In [17], a delay-bounded type-II hybrid ARQ scheme us-ing BCH codes is investigated for delivering H.263 coded

video over indoor wireless ATM link. Hybrid ARQ makesuse of both FEC and ARQ to achieve near optimal through-put and reliability. Simulation results show that significantimprovement in video quality can be achieved.

6. Conclusions

We investigated the issue of error control in wirelesscommunication networks. We examined the alternativesavailable for providing a reliable end-to-end communica-tion in wireless environments, and discussed their trade-offs. The channel conditions are different in different wire-less environments such as indoor and outdoor, high mobilespeed and low mobile speed. QoS requirements are alsodependent on the applications. An overall optimal solutiondoes not exist. A solution should be based on the applica-tion, the environment and the QoS requirements to designthe error control scheme and achieve the best solution.

References

[1] A. Acampora, Wireless ATM: A perspective on issues and prospects,IEEE Personal Communications (August 1996).

[2] S. Aikawa et al., Forward error correction schemes for wireless ATMsystems, in: Proc. IEEE ICC ’96 (1996) p. 454.

[3] E. Ayanoglu et al., AIRMAIL: A link-layer protocol for wirelessnetworks, Wireless Networks 1(1) (February 1995).


[4] E. Ayanoglu et al., Wireless ATM: Limits, Challenges, and Propos-als, IEEE Personal Communications (August 1996).

[5] E. Ayanoglu et al., Forward error control for MPEG-2 video trans-port in a wireless ATM LAN, Mobile Networks and Applications(September 1996).

[6] E. Ayanoglu et al., Forward error control for MPEG-2 video transportin a wireless ATM LAN, in: Proc. ICIP’ 96 (1996).

[7] J.B. Cain et al., A recommended error control architecture for ATMnetworks with wireless links, IEEE Journal on Selected Areas inCommunications 15(1) (January 1997).

[8] G. Clark and J. Cain, Error-Correction Coding for Digital Commu-nications (Plenum Press, New York, 1981).

[9] G. Clark, J. Cain and J. Geist, Punctured convolutional codes ofrate (n− 1)/n and simplified maximum likelihood decoding, IEEETransactions on Information Theory 25 (1979) 97–110.

[10] Group Special Mobile (GSM) Recommendation (April 1988).[11] D. Haccoun and G. Begin, High-rate punctured convolutional codes

for Viterbi and sequential decoding, IEEE Transactions on Commu-nications 31(11) (1989) 1113–1125.

[12] J. Hagenauer, Rate-compatible punctured convolutional codes(RCPC codes) and their applications, IEEE Transactions on Com-munications 36 (1988) 389–400.

[13] S. Kallel and D. Haccoun, Generalized type-II hybrid ARQ schemeusing punctured convolutional coding, IEEE Transactions on Com-munications 38(11) (1990) 1938–1846.

[14] L. Lee, Concatenated coding systems employing a unit-memory con-volutional code and a byte-oriented decoding algorithm, IEEE Trans-actions on Communications 25(10) (1977) 1064–1074.

[15] S. Lim et al., Cell loss reduction by cell unit interleaving in wirelessATM Networks, in: IEEE ICC ’96 (1996) p. 449.

[16] S. Lin and D.J. Costello Jr, Error Control Coding: Fundamentalsand Applications (Prentice-Hall, Englewood Cliffs, NJ, 1983).

[17] H. Liu and M. El Zarki, Delay bounded type-II hybrid ARQ forvideo transmission over wireless channel, in: Proc. Conference onInformation Sciences and Systems, Princeton, NJ (March 1996).

[18] L. Lugand, D. Costello and R. Deng, Parity retransmission hybridARQ using rate 1/2 convolutional codes on a nonstationary channel,IEEE Transactions on Communications 37(4) (1989) 755–765.

[19] A. Michelson and A. Levesque, Error-Control Techniques for DigitalCommunication (Wiley, New York, 1985).

[20] M. Nakamura and T. Kodama, Performance evaluation for ARQschemes in power and/or bandwidth limited systems, Transactionsof IEICE 72(5) (1989) 491–501.

[21] R.O. Onvural, Asynchronous Transfer Mode Networks: PerformanceIssues (Artech House, 1993).

[22] J.E. Padgett, C.G. Gunther and T. Hattori, Overview of wirelesspersonal communications, IEEE Communications Magazine 33(1)(1995) 28–41.

[23] J.G. Proakis, Digital Communications (McGraw-Hill, 1989).[24] D. Raychaudhuri, Wireless ATM networks: Architecture, system

design and prototyping, IEEE Personal Communications (August1996).

[25] Special Issue: Wireless ATM, IEEE Personal Communications (Au-gust 1996).

[26] Special Issue: Wireless ATM, Mobile Networking and Applications(September 1996).

[27] Special Issue: Wireless ATM, IEEE Journal on Selected Areas inCommunications (January 1997).

[28] R. Steele, Mobile Radio Communications (Pentech Press, London,1992).

[29] TIA/EIA IS-95, Mobile Station-Base Station Compatibility Stan-dard for Dual Mode Wide-Band Spread-Spectrum Cellular Systems,Telecommunications Industry Association (1992).

[30] TIA/EIA IS-99, Data Services Option Standard for Wideband SpreadSpectrum Digital Cellular System, Telecommunications Industry As-sociation (September 1994).

[31] Y. Wang and S. Lin, A modified Selective-Repeat type-II hybridARQ system and its performance analysis, IEEE Transactions on

Communications 31(5) (1983) 124–133.[32] S.B. Wicker, Reed–Solomon error control coding for Rayleigh fading

channels with feedback, IEEE Transactions on Vehicular Technology41(2) (1992) 124–133.

[33] H. Xie et al., Data link control for wireless ATM access channels,in: Proc. ICUPC ’95 (1995).

[34] M. Zorzi and R.R. Rao, Capture and retransmission control in mobileradio, IEEE Journal on Selected Areas in Communications 12(8)(1994) 1289–1298.

Hang Liu received the B.S. from Tianjin Uni-versity, China, in 1985, and the M.S. from theUniversity of New Orleans, New Orleans, LA, in1992. He is currently a Ph.D. candidate in theDepartment of Electrical Engineering, Universityof Pennsylvania. His research interests includevideo compression and communications, wirelessnetworking, ATM based networks and digital sig-nal processing.E-mail: [email protected]

Hairuo Ma received his B.S. from Tsinghua University, Beijing, P.R.China, and his M.S. from the University of Pennsylvania, both in elec-trical engineering, in 1993 and 1995, respectively. In 1996, he was asoftware engineer at DTI, Maryland. Currently, he is a Ph.D. candidatein the Department of Electrical Engineering, Univ. of Penn. His researchinterests include wireless networking, wireless ATM, broadband serviceto the home and multiresolution transmission.E-mail: [email protected]

Magda El Zarki received the B.E.E. degree fromCairo University, Egypt, in 1979, and the M.S.and Ph.D. degrees in electrical engineering fromColumbia University, New York, NY, in 1981 and1987, respectively. She worked from 1981 to 1983as a communication network planner in the De-partment of International Telecommunications atCitibank in New York. She joined Columbia Uni-versity in 1983 as a research assistant in the Com-puter Communications Research Laboratory where

she was involved in the design and development of an integrated local areanetwork testbed called MAGNET. In 1988 she joined the faculty of theDepartment of Electrical Engineering of the University of Pennsylvania,teaching courses and conducting research in the field of telecommunica-tions, where she currently serves as an associate professor. She also holdsa secondary appointment in the Department of Computer and InformationSciences. In January 1993, she was appointed as a part-time professor ofTelecommunication Networks in the Faculty of Electrical Engineering atDelft University of Technology, in Delft, The Netherlands. Dr. El Zarki isa member of the ACM, IEEE and Sigmaa Xi. She is actively involved inmany of their sponsored conferences and journals. She was the TechnicalProgram Chair of IEEE INFOCOM ’94.E-mail: [email protected]

Sanjay Gupta received his Ph.D. in systems in1993 and M.S. degree in electrical engineeringin 1989, both from the University of Pennsylva-niaa. He received his B. Tech. degree in electricalengineering in 1988 from the Indian Institute ofTechnology, Kanpur. He joined the Departmentof Electrical and Computer Engineering at IllinoisInstitute of Technology in 1993 as an AssiatantProfessor. He was a visiting research scholar atHong Kong University of Science and Technol-


ogy during the summer of 1995 and 1996. He is currently employed atMotorola, where he is working on UMTS and GSM. His oher researchinterests include wireless local area networks, ATM based broadband net-works, management and control of communication networks, and sto-

chastic modeling and simulation. He has served as a Technical ProgramCommittee member for the IEEE Infocom conferences since 1993 and theIEEE Vehicular Technology Conference 1995.E-mail: [email protected]

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