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Paper 12-Cross Layer QoS Support Architecture With Integrated CAC and Scheduling Algorithms for WiMAX BWA Networks

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  • 8/3/2019 Paper 12-Cross Layer QoS Support Architecture With Integrated CAC and Scheduling Algorithms for WiMAX BWA Net


  • 8/3/2019 Paper 12-Cross Layer QoS Support Architecture With Integrated CAC and Scheduling Algorithms for WiMAX BWA Net


    (IJACSA) International Journal of Advanced Computer Science and Applications,

    Vol. 3, No. 1, 2012

    77 | P a g e

    feedback received from other layers to optimize the relevantparameters in the current layer to achieve the optimumperformance. Although the cross layer design is an evolvingarea of research, considerable amount of work has already beendone in this area [1].

    In this paper, information from the MAC layer is used tooptimize the parameter at PHY layer. Among severalalternatives, the IEEE 802.16 PHY layer standard realizes the

    usage of Orthogonal Frequency Division Multiplexing(OFDM) in order to mitigate the adverse effects of frequencyselective multi-path fading and to efficiently contrast Inter-Symbol and Inter Carrier Interferences (ISI and ICI) [9]. Inaddition, PHY layer also supports variable channel bandwidth,different FFT sizes, multiple cyclic prefix times and differentmodulation schemes such as QPSK, 16QAM and 64QAM withconvolutional encoding at various coding rates [10]. On theother hand, Call Admission Control (CAC) mechanism [11-19]and Scheduling mechanism [17-23] are the important wings ofWiMAX QoS framework at MAC layer. A CAC algorithm atbase station (BS) will admit a subscriber station (SS) into thenetwork if the BS ensures the minimum QoS requirement ofthe SS without degrading the existing QoS of other SSs in the


    Providing CAC in IEEE 802.16 BWA networks guaranteesthe necessary QoS of different types of connections and at thesame time decreases the Blocking Probability (BP) [13],Dropping Probability (DP) [14] and Outage Probability (OP)[24] for all types of connections. These QoS parameters can beused as feedback information to the PHY layer in order toselect an appropriate Modulation and Coding Scheme (MCS)for better network performance. Again, scheduling algorithm atSS will distribute the bandwidth of the selected MCS amongthe real-time and the non-real-time traffic, based on the type ofusers in the network and their QoS requirements. Scheduling inthe uplink direction is tedious because of required bandwidth

    request, bandwidth grant and transmission of data of each flowwhich affect the real-time application due to large Round TripDelay (RTD) [25, 26].

    The scheduling algorithm involves in fair allocation of thebandwidth among the users, determining their transmissionorder and enhancement of bandwidth utilization. Fairness refersto the equal allocation of network resources among the varioususers operating in both good and bad channel states. In this

    paper, fairness has been quantified using Jains Fairness Index[27].

    A. Background literatureA significant number of proposals on cross layer designs

    have been found in recent literature. Many of them refer to

    feedback mechanisms between the PHY and MAC layers. In[28] authors have introduced a cross layer approach forcalculating the QoS indicators (blocking rates, download timeand bit error rates) taking into account the PHY layerconditions (modulation and coding, propagation and MIMO),the MAC layer radio resource management algorithms and thehigher layer traffic characteristics. Authors have alsoconsidered different admission control schemes and studied theimpact of adaptive modulation and coding on the performanceof elastic traffic. But no packet scheduling algorithms for fair

    allocation of bandwidth among the traffic sources have beenconsidered. Also optimum range of Signal to Noise Ratio(SNR) for adaptive MCS in the networks has not beendetermined.

    A framework of memory less scheduling policies based onchannel quality states, buffer occupancy states andretransmission number states has been provided in [29]. Thescheduling policies combine AMC (Adaptive Modulation and

    Coding) and ARQ (Automatic Repeat Request) in a cross layerfashion that produces a good throughput performance withreduced average delay. However, the authors have notconsidered any CAC algorithm for connection management inthe networks.

    Similar to [29], [30] proposes a scheduling algorithm onlyat the MAC layer for multiple connections with diverse QoSrequirements, where each connection employs AMC scheme atthe PHY layer over wireless fading channels. A priorityfunction is defined for each connection admitted in the system,which is updated dynamically depending on the wirelesschannel quality, QoS satisfaction, and services across all layers.The connection with highest priority is scheduled at each time.

    At the MAC layer, each connection belongs to a single serviceclass and is associated with a set of QoS parameters thatquantify its characteristics.

    A cross layer optimization mechanism for multimediatraffic over IEEE 802.16 BWA networks has been proposed in[31, 32].The main functionality of the cross layer optimizationmechanism resides at the BS part. The authors have used adecision algorithm at the BS part that relies on the values oftwo major QoS parameters, i.e., the packet loss rate and themean delay. These QoS parameters activate proper adjustmentof the modulation and/or the media coding rate, aiming atimproving QoS and system throughput. However, this paperhas not considered proper CAC and scheduling mechanisms forthe delay sensitive real-time traffic flow at MAC layer. The

    authors have also not evaluated the optimum range of SNR inorder to uniformly control modulation and data encoding rates.

    A cross layer scheduler that employs AMC scheme at thePHY layer, according to the SNR on wireless fading channelshas been described in [33]. The authors have defined costfunction for each kind of multimedia connections based on itsservice status, throughput or deadline in MAC layer to achievean optimum tradeoff between the throughput and fairness.Though the authors have included a suitable schedulingalgorithm at the MAC layer but the authors have not consideredany CAC algorithm.

    [34] proposes a cross layer optimization architecture forWiMAX system. It consists of a Cross layer Optimizer (CLO),

    which acts as an interface between MAC and PHY layers. TheCLO gathers and optimizes the parameters from both layers toachieve optimum performance gain. The CLO gets the channelcondition information from the PHY layer and bandwidthrequests and queue length information from the MAC layer sothat it can switch to different burst profile for differentmodulation and coding schemes. In this case also, the authorshave not specified proper CAC and scheduling mechanism atthe MAC layer. Moreover, no optimum range of SNR has beentaken into account in CLO while switching to different MCS.

  • 8/3/2019 Paper 12-Cross Layer QoS Support Architecture With Integrated CAC and Scheduling Algorithms for WiMAX BWA Net


    (IJACSA) International Journal of Advanced Computer Science and Applications,

    Vol. 3, No. 1, 2012

    78 | P a g e

    Another cross layer approach as provided in [3], analysesseveral QoS parameters that include the bit rate and the biterror rate (BER) in the PHY layer, and packet averagethroughput/delay and packet maximum delay in the link layer.Authors show that dynamic OFDMA has a stronger potential tosupport multimedia transmission than dynamic OFDM-TDMA.Authors have taken care of proper scheduling, throughput anddelay guarantee of traffic flows ignoring the CAC mechanismat MAC layer.

    [4] describes a polling based uplink scheduling schemes forTCP based applications in a multipoint to-point fixedbroadband IEEE 802.16 BWA network. This scheme adaptsthe transmission rates between the SSs and the BS dynamicallyusing adaptive modulation technique. With adaptivemodulation, the uplink scheduling algorithm helps to achievehigher data transmission rate, fairness in slot assignment and inthe amount of data transmission.

    B. ContributionThe novelty of our work focuses on the dynamic selection

    of MCS based on Eb/N0 ratio of the concerned connections andrelevant feedback information obtained from the MAC layer in

    terms of New Connection Blocking Probability (NCBP), Handoff Connection Dropping Probability (HCDP) and ConnectionOutage Probability (COP) to employ the most appropriateMCS in the network. The target values of the feedbackinformation changes the selection of modulation and codingrate dynamically based on optimum range of Eb/N0 ratio of theconnections to enable a flexible use of the network resources.The effect of Eb/N0 ratio has been observed on NCBP, HCDPand COP for all the relevant connection types under variousMCS by means of exhaustive simulation. The simulationresults help to determine the optimum range of Eb/N0 ratio forall the connections with appropriate MCS. It has been observedthat the integrated CAC and Scheduling algorithm maximizesthe utilization and fair allocation of the system resources for all

    types of MCS and provide better QoS support with reducedNCBP, HCDP and COP in the IEEE 802.16 BWA networks.

    Since there is also a possibility that the wireless channeldeteriorates or becomes unavailable at certain instant of time,the CAC and scheduling algorithms at the MAC layer, whichhas been left undefined in the standard, can get properknowledge of the channel condition, in terms of SINR of theconnections. Thereby, only the connection with a good channelcondition is admitted and scheduled for transmission to achievemore gain in bandwidth utilization and fairness index.

    An analytical model based on Continuous Time MarkovChain (CTMC) [35] is developed for the more realistic analysisof QoS parameters for the performance evaluati

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