DefenseElectronics

MIMO: The next revolution in wireless data communicationsWhile providing a technical overview of MIMO and its different variants, and quantifying some of its benefits in relevant scenarios in military tactical communications, the article also identifies key capabilities that efficient MIMO development/evaluation platforms must offer.

By Babak Daneshrad

Multi-antenna based multi-input multi-output (MIMO) communications first

burst onto the scene in the mid 1990s when researchers at Bell Labs and Stanford were looking for ways to increase system through-put without increasing bandwidth. In the de-cade since, thousands of research papers have been written on the topic dealing with both physical layer (PHY) and network layer rami-fications of the technology. MIMO has gone through the adoption curve for commercial wireless systems to the point that today, all high throughput commercial standards (i.e., WiMax, Wi-Fi, cellular, etc.) have adopted MIMO as part of the optional, if not manda-tory, portions of their standards. The adoption of MIMO into military wireless communica-tions systems has to some extent lagged its adoption in the commercial arena. To date, the largest DoD-funded effort with a uniquely MIMO-centric focus is the Defense Advanced Research Projects Agency (DARPA) Mobile Networked MIMO (MNM) program. This program is a multiyear, multimillion-dollar effort that looks to exploit MIMO techniques to (a) provide reliable communications in urban canyons; (b) significantly extend the reach of conventional single-antenna wireless systems; (c) improve reliability of individual links: and (d) enhance mobile ad-hoc network (MANET) throughput rate by 10x or more compared to current SISO-based radios. Lucent Technologies was the performer on

the first phase of the program, whereas Silvus Technologies was chosen as the performer on the second and third phases of the program.

This article will provide a technical over-view of MIMO and its different variants, as well as quantify some of its benefits in relevant scenarios in military tactical communications. Finally we will identify key capabilities that efficient MIMO development/evaluation plat-forms must offer to the marketplace.

Introduction to MIMOThe pioneering work by Telatar, Foschini

and Gans at Bell Labs demonstrated that MIMO in a wireless communication system can greatly improve performance, as much as one order of magnitude or more, without requiring any additional bandwidth.

A MIMO wireless system consists of N transmit antennas and M receive antennas. However, unlike phased array systems where a single information stream, say x(t), is trans-mitted on all transmitters and then received at the receiver antennas, MIMO systems trans-mit different information streams, say x(t), y(t), z(t), on each transmit antenna. These are independent information streams being sent simultaneously and in the same frequency band. At first glance, one might say that the transmitted signals interfere with one another. In reality, however, the signal arriving at each receiver antenna will be a linear combination of the N transmitted signals.

Figure 1 shows a MIMO system with three transmit and three receive antennas. The re-ceived signals r1(t), r2(t), r3(t) at each of the three received antennas are a linear combina-tion of x(t), y(t), z(t). The coefficients {aij} represent the channel weights correspond-ing to the attenuation seen between each transmit-receive antenna pair. The affect is that we have a system of three equations and three unknowns as shown below.

r A

x

y

z

=

In general, the matrix, A, of channel coef-ficients {aij} must be invertible for MIMO systems to live up to their promise. It has been proven that the likelihood for A to be invert-ible increases as the number of multipaths and reflections in the vicinity of the transmitter or receiver increases. The impact of this is that in a Rayleigh fading environment with spatial independence, there are essentially NM levels of diversity available and there are min(N,M) independent parallel channels that can be established. Increases in the diversity order results in significant reductions in the total transmit power for the same level of performance. On the other hand, an increase in the number of parallel channels translates into an increase in the achievable data rate within the same bandwidth.

Let us now quantify the benefits of MIMO-based sys-tems operating in a typical Rayliegh fading wireless channel. Figure 2 compares the achievable 95-percentile capacity (minimum capacity achieved over 95 percent of wireless channels encoun-tered, or in other words, given a channel, there is a 95 percent chance that the capacity of that channel is higher than the capacity shown in the plot) for single antenna systems (yellow dot), for a phased array multi-antenna system

F2-Figure 1

Modulator

Modulator

Modulator

x(n) x(t)

y(n)y(t)

z(n)z(t)

r1(t) = a11x(t) + a12y(t) + a13z(t)

r3(t) = a31x(t) + a32y(t) + a33z(t)

x(n)

y(n)

z(n)

MIMOreceiver

Figure 1. MIMO transmission and reception in a dispersive environment. In a MIMO system, different information is transmitted simultaneously on each transmit antenna.

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(blue curve), and for MIMO systems (red curve). As shown, the capacity of the phased array system grows logarithmically with increasing antenna array size, whereas the capacity of the MIMO system grows linearly. With four antennas, the phase array system provides a capacity of 8 bps/Hz, whereas the MIMO system provides a capacity of 19 bps/Hz. It is also worth noting that in a phased array system, the array coefficients must be calculated to point the beam in the “best direc-tion.” This is quite difficult to do when the transmitter is inside the hull of an aircraft where the signal undergoes many reflections before it emerges from the aircraft and lands at the receiver. MIMO systems do not suffer from this problem as the geometry of the environment and position of the reflectors are automati-cally taken into account during the decoding of the MIMO signal.

The benefits of MIMO will now be considered in a different light. Assume that there is a fixed capacity that is desired, say 1 bps/Hz, and ask the question, “How much total transmit power is needed to achieve a 95-percentile capacity of 1 bps/Hz?” The results are summarized in Table 1. As is seen from the table, as the number of antennas increase in a MIMO system, less and less receive power is needed to achieve the same data throughput rate. This is an important finding as it is the key property that is relied upon to combat the attenuation associated with getting the signal out of the aircraft hull. So if a conventional single antenna system required 1 Watt of transmit power to achieve a certain throughput, then an 8 x 8 MIMO system would require only 6 mW of power to achieve the same performance.

A multiplicity of MIMO modesThe appeal of spatial multiplexing

MIMO systems has captured many people’s attention. This has been taken to the ex-treme whereby spatial multiplexing MIMO schemes have been suggested to solve any and all wireless communication issues. In fact, there are four unique multi-antenna MIMO techniques available to the system designer as follows:• Spatial multiplexing (SM-MIMO). Mul-

tiple antennas are used to create spatially independent links along the eigen-modes of the wireless channel. In SM systems, throughput is increased by sending differ-ent data on the different transmit antennas. As such SM-MIMO can result in much improved throughput without increasing

bandwidth. The downside to SM is the need for highly complex matrix inversion operations in the receiver, and the added sensitivity to impairments when the system is driven into “full-multiplexing” (number of spatial streams is equal to the number of transmit antennas which in turn is equal to the number of receive antennas) mode of operation.

• Space-time coding (STC-MIMO). Space-time coding systems look to provide coding gain by introducing redundancy along the three signaling axes defined as time, frequency and space. They can also be used to provide transmit diversity gain. Compared to spatial multiplexing systems, STC-MIMO systems provide robustness of communications without providing signifi-cant throughput gains. Moreover, they are well suited to asymmetric situations where the transmitter may have more antennas at its disposal than the receiver.

• Diversity systems (DIV-MIMO). Diversity is a traditional form of multi-antenna pro-cessing that looks to counteract fast fading effects by creating independent channels between the TX and RX, transmitting the same signal on all independent channels and optimally combining the received signals.

• Smart antenna (SA-MIMO) systems are best described as adaptive phased array

antenna systems that can adap-tively beamform or beam-null in a particular direction.

Leveraging MIMO for the military

The true benefit of MIMO is not simply its ability to increase throughput or reliability, rather, when properly married with the other elements of the radio, MIMO enables a truly mode-rich radio--one that is ideal for opera-tion in non-line-of-sight (NLOS) environments found in urban can-yons and forested regions. This allows a MIMO-enabled radio to exhibit elasticity beyond that of conventional single-antenna radios, and to better adapt to the needs of the war fighter and the operational environment.

Examples of use in military-grade com-munications are: • For communication centers (i.e., ground-

based command posts, ship-to-shore or ship-to-ship communication), a high throughput mode can be used to transfer data at speeds greater than 100 Mbps.

• In a NLOS environment, the radio can use a physical mode, which lowers the data rate to 10 Mbps in exchange for higher quality of service (QoS). A platoon of tanks proceeding down separate streets in an urban environment can continue cross-communications.

• In an environment where jammers are used in an attempt to disrupt communication, a mode sending redundant packets across multiple paths can be used to ensure that uncorrupted data reaches the receiver. Integrity and consistency saves lives and contributes to Mission Success.

• In a mobile environment (i.e., tanks or Hum-vees advancing across open terrain, surveil-lance UAVs scouring an area of interest), yet another mode can be used to enable high data rates between fast-moving vehicles.

• For covert applications, some solutions can exploit MIMO modes to transmit at a reduced rate while using an ultra low transmit power mode to conceal its elec-tronic signature.

• For real-time video surveillance applica-tions (i.e., border or perimeter monitoring, real-time battlefield monitoring), a high throughput, high QoS mode can be used.

• For mesh networks, some solutions take advantage of all of the reflections (i.e., signals bouncing off hundreds of armored vehicles) to improve performance, as op-posed to current single antenna systems, which cannot function in high-demand, high-interference environments.

Table 1. Receive SNR required to achieve a 95-percentile capacity of 1bps/Hz.

Antenna Configuration MIMO

SISO (1x1) 12.8 dB

2x2 1.2 dB

4x4 –4.9 dB

8x8 –9.3 dB

Figure 2. MIMO capacity increases with array size, whereas phased ar-ray smart antenna systems only improve logarithmically.

F2-Figure 2

50

45

40

35

30

25

20

15

10

5

0

Cap

acity

(bp

s/H

z)

Number of receive antennas1 2 103 4 5 6 7 8 9

50

45

40

35

30

25

20

15

10

5

Number of receive antennas1 2 103 4 5 6 7 8 9

5

0011

95% outage capacity

MIMO systemNumber of Tx antenna =Number of Rx antenna

MIMO systemNumber of Tx antenna =Number of Rx antenna

Traditional 1x1SISO system does not

improve withmore antennas

Traditional 1x1SISO system does not

improve withmore antennas

Smart antenna arraynumber of transmitantenna �xed at 1

Smart antenna arraynumber of transmitantenna �xed at 1

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Validating MIMO in the fi eld

Today, suppliers must be able to provide complete radio modules comprised of an antenna, RF transceiver, a complete packet-based baseband processing engine, and a robust and intuitive API (Figure 3). Such solutions, like the SC2000 from Silvus Technologies, are ideal for networking applications, as the radio unit can be com-manded by any medium ac-cess control (MAC) protocol. The user (or user program) can dictate radio parameters on a per-packet basis. With 300+ operating modes to choose from, such platforms put per packet reconfi gurabil-ity in the hands of the user.

This richness of modes can be realized through the manipulation of 10 individual parameters, each of which can take on a range of values. Table 2 summarizes the 10 parameters and their range of values.

The platform approach has two FPGAs (one for the MAC and another for the PHY) along with a PowerPC processor. Devel-opers can interface through a USB 2.0 or Ethernet interface. The platform comes with a 4 x 4 PHY embedded in one of the FPGAs and can be populated with up to four radio boards. These solutions provide increased performance, cost effectiveness and overall effi ciency in the development of MIMO-based systems. A complete FPGA rapid-prototyping system supports hardware-in-the-loop co-simulation and real-time processing. In addition, it cuts development

time by 1, quickly validating concepts and 2, integrating a MIMO-based PHY/MAC onto users’ application-specifi c physical realiza-tion of MIMO IP.

The baseline design delivered onto the tool is that of an 802.11n compliant PHY+MAC, however, this baseline design can be augmented to include interference mitigation protocols, and variable bandwidth capability. Additionally, FPGA-based video codecs could also be implemented on the platform to enable wireless video distribu-tion applications. The tool can also be used during design to confi gure the end system, as the evaluation board could be used in an experimental framework to identify the optimum mode to use in a given environ-ment. As an example, let us consider a user

wanting to identify the most optimum mode of transmission within a given environment. The evaluation board would allow the user complete confi gurability and would allow him or her to easily cycle through hundreds of parameter confi gurations in order to iden-tify the most optimum set of link parameters for the situation at hand.

The evaluation platform could be used to validate the IP and to interface it to other elements within the customer’s SoC. When put into the hands of researchers, the plat-form is an ideal tool to enable validation and experimentation with advanced MAC and networking protocols that look to leverage OFDM and/or MIMO based communica-tions. Within the military sector, the platform could be used to validate and quantify the benefi ts of MIMO based communications as a function of mission requirements and environmental conditions.

Figure 3. Manufacturers today need to offer complete radio modules and include every functional block inside the dotted boundary. The user can substitute a customized RF front end.

F2-Figure 3

A/D

D/A

A/DA/DA/D

D/AAAAAAA

A/DA/DA/D

D/A

AAAAAAAAA

A/D

D/AAA/D

D/ASingle channel

Mod/Demod

MIMOEncode/decode

FECencode

FECdecode

RF CNTL Digital

Any RF

API

User

Silvus PHYFully con�gurable universal 4 x 4 MIMO OFDM PHY

Complete PHY CNTLvia API

CNTL to RF for AGC,calibrate, RF carrier

A

MAC

Table 2. List of example PHY parameters under direct user control.

Parameter Range

Bandwidth 5, 10, 20 MHz

Number of antennas 1x1, 1x2, … 2x4, …4x4

Type of antenna processing Spatial multiplexing, Space-time coding diversity Hybrid Tx diversity and spatial-multiplexingRx diversityEigen beamforming & beamnulling at RxSmart antenna

Modulation OFDM (64 point FFT)

Constellation size 2-, 4-, 16-, 64-QAM

Coding rate 1/2, 2/3, 3/4, 5/6

Spatial multiplexing decoder Modifi ed MMSE

Number of spatial streams 1,2,4

Transmit power 0 dBm to 36 dBm

Packet size 2 bytes to 64 kbytes

ABOUT THE AUTHOR

Babak Daneshrad is president and CEO of Silvus Technologies. He has been a professor with the UCLA Electrical Engineering Department since 1996. He is well published in the area of wireless communications, with an emphasis on experimental multi-antenna systems. In 2001, he co-founded Innovics Wireless where he served as the CEO, chairman, and later CTO. Innovics, a specialized fab-less semiconductor company, raised $14 million in venture capital and developed the fi rst multi-antenna, diversity-enabled WCDMA-3G mobile terminal ASIC.

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