2010 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery Effect of Finite State AMC on the Practicality of Dual Feedback Bandwidth Request Control Nguyen Quoc Tuan University of Engineering and Technology, Vietnam National University, Hanoi tuannq@vnu.edu.vn Dinh-Thong Nguyen, Member IEEE Faculty of Engineering and Information Technology, University of Technology, Sydney dinh-thong.nguyen@eng.uts.edu.au Abstract- Dual feedback control algorithm has proved to allow the base station to respond quickly and efficiently to the uplink bandwidth request in broadband wireless access (BWA) networks [2][3] In this algorithm the bandwidth request is calculated based on both the length of the backlogged queue and the mismatch between packet arrival and service rates However, the physical channel quality, SNR, does not play any role in the algorithm; therefore the algorithm is suboptimal with respect to bandwidth utilization Under fading conditions modern BWA networks employ adaptive modulation and coding (AMC) which has only a finite number of discrete service rates to grant to subscribers In this paper, we examine the effect of AMC in WiMAX using the Finite State Markov Channel model on the practicality and efficiency of the dual feedback bandwidth request control algorithm I Traditional bandwidth scheduling algorithms in multi-users wireless networks are based solely on the user’s physical channel quality in terms of signal-to noise ratio (SNR) This often results in a significant mismatch between the packet arrival rate at the SS and the rate at which its packets are being serviced by the network, i.e being transmitted, hence creating either a backlog in the queue at the SS which is undesirable for the SS, or an empty queue which is undesirable for network bandwidth efficiency However the response to a bandwidth request based on information about the backlogged queue length alone suffers from the usual feedback delay in the time-division duplex (TDD) mode of transmission between the BS and the SSs Because of this, a group of researchers at Samsung Electronics has recently proposed a bandwidth request-allocation control algorithm for real-time services [2] based on dual feedback of information from both rate mismatch and queue length mismatch which is a measure of queue length deviation from a desired length to keep the delay to within the QoS requirement The main virtue of dual feedback algorithm is that the SS uses the rate mismatch as a predictive indicator on the queue length variation in order to calculate the next bandwidth request, thus enhancing the reliability of the request The algorithm requires the SS to be more proactive and to cooperate with the BS in working out together a more efficient bandwidth request INTRODUCTION The central challenging task in design and operation of a multi-users broadband wireless access (BWA) network is to come up with a fair and efficient scheduling of the network’s finite bandwidth to users of different types of traffic, satisfying the agreed QoS requirements In order to support QoS for various types of traffic, IEEE 802.16 (commonly known as WiMAX) medium access control (MAC) protocol [1] defines bandwidth request-allocation mechanisms for five types of scheduling classes: Unsolicited Grant Service (UGS) being suitable for constant bit rate services such as VoIP, realtime Polling Service (rtPS) being suitable for variable bit rate traffic such as MPEG video, extended real-time Polling Service (ertPS) as a compromise for delay sensitivity and bandwidth efficiency, non-real-time Polling Service (nrtPS), and Best-Effort (BE) The above are the general scheduling mechanisms that the base station (BS) uses to allocate bandwidth to subscriber stations (SS), but the detailed algorithm to decide how much bandwidth is allocated to a request is not standardized but is left to the innovation of proprietary implementations by equipment vendors and/or network operators 978-0-7695-4235-5/10 $26.00 © 2010 IEEE DOI 10.1109/CyberC.2010.69 The suboptimal nature of the dual feedback bandwidth request control algorithm proposed in [2] is that the physical channel quality, i.e the SNR, does not play any role in the algorithm In modern BWA networks, adaptive modulation and coding (AMC) is used by the BS to assign a certain modulation and coding scheme to the SS in accordance with the SNR of the SS’s link in order to optimize the system’s bandwidth efficiency, hence its throughput The WiMAX fading channel is modeled using a Finite State Markov Channel (FSMC) model [5] corresponding to the finite number of combination of modulation and coding schemes recommended in the 802.16 standards Thus the BS operates only with a finite number of discrete optimal spectral efficiencies c(n) If the granted bandwidth BW is fixed such as 352 where l (bytes) is the average packet size and T0 represents any additional delay apart from queuing delay in the UGS scheduling, service rates s(n)=BW*c(n), being available for allocation to the SSs will also be of finite step changes, and these rates often not match those calculated from the dual feedback algorithm under the optimistic assumption that the BS can, most of the time, satisfy the bandwidth requests Thus the granted bandwidth can only be time varying, b(n), and the reserved bandwidth agreed on admission can only be based on the statistical average of b(n) This is only an example in which the above dual feedback algorithm is not practical for UGS implementation From our experience, b(n) can become quite large that even ertPS scheduling cannot practically satisfy the request It is important to realize that the fixed system radio resource that BS has the job to schedule to the SSs is the system bandwidth in Hz, not the service rates Let Q(n) be the queue length, a(n) and s(n) be the packet arrival rate (to the wireless channel) and the packet departure rate (from the channel), i.e service rate by the channel, respectively, at time instant nTa; the total bandwidth request at time nTa be B(n) and the additional request be ΔB(n); then in a dual feedback system ΔB(n) has two components: one deduced from the queue length mismatch eq(n)=q(n)-Qref and the other from the transmission rate mismatch er(n)=a(n)-s(n), i.e ΔB( n ) = K q e q ( n ) + K e r ( n ) where Kq and Kr are r constants [2] By observing that the unit of eq(n) is in byte while that of er(n) is in byte per second, we can see that Kr in ∆B(n) above is not a constant but has a unit of time depending on service interval Ta We therefore have proposed in to modify the algorithm to [3] In [5] we have already examined this issue and have proved that the stability condition given for the continuous-time transfer function cannot guarantee the stability of its discretetime implementation of the algorithm In this paper, we propose a simple technique to calculate the reserved bandwidth for a given arrival traffic under a given channel fading condition Obviously, the technique is most suitable for exrtPS to update its bandwidth request Fortunately, the proposed calculated reserved bandwidth is near optimal in terms of PHY and MAC layers, and furthermore it is independent of the proposed dual feedback algorithm in [2] ΔB ( n) = K q e q ( n) + C r Ta e r ( n ) It is obvious that rate mismatch directly creates fluctuation in the queue length q(n), hence a fluctuation in the queue length mismatch eq(n), i.e er ( n ) = a ( n) − s ( n ) The rest of the paper is organized as follows: Section II presents a summary of the bandwidth request control algorithm based on dual feedback, including its stability in the discrete-time (implementation) domain In Section III, a brief explanation of the 10-state Finite State Markov Channel model proposed for WiMAX in [5] is given Section IV presents the simulation setup and results The paper ends with a brief conclusion in Section V II = Ta l T a [ q ( n) − q ( n − 1)] = [e ( n) − e ( n − 1)] q q T a (3) Under strict admission control and priority scheduling for real-time traffic, the authors in [2] assume that the BS can mostly satisfy bandwidth request for real-time services by allocating bandwidth at a rate more or less equal to the bandwidth requested by the SS on average, In this section we present a summary of the dual feedback algorithm in discrete-time domain for bandwidth request control proposed in [2] Discrete-time implementation of hardware and software is the ultimate objective of modern electronic and telecommunication systems Therefore the stability of any control algorithm depends ultimately on its system transfer function G(z) in the z-domain The algorithm assumes that the bandwidth allocation interval Ta (sec) is equal to the packetization interval of the real time service, which is constant The relationship between the tolerable MAC-toMAC target delay, Tref, of the service and the corresponding target transmission queue length, Qref (bytes), is Qref = The relationship in (3) is the essence of the dual feedback algorithm DUAL FEEDBACK ALGORITHM FOR UPLINK BANDWIDTH REQUEST Tref − T0 (2) s(n) ≈ α B ( n − 1) (4) Ta As we have mentioned in the Introduction, this assumption is neither realistic in a heavily subscribed network, nor practical in a modern network in which adaptive modulation and coding is used in fading environment As will be seen later on in this section, α plays an important role in the stability of the system, yet in [2] it is simply assumed to be Taking z-transform of (3) and (4) then combining them, we have (1) A( z ) − α 353 z −1 B ( z ) − z −1 Eq ( z ) = Ta Ta (5) From the z-transform of (2) and (3), we have ΔB( z) = B( z)(1 − z −1 ) = Kq Eq ( z) + Cr Eq ( z).(1 − z −1 ) algorithm is that the physical channel quality, i.e the SNR, does not play any role in the algorithm Yet in modern BWA networks, adaptive modulation and coding (AMC) is used by the BS to assign an appropriate modulation and coding scheme to the SS in accordance with the SNR of the SS’s link in order to optimize the system’s bandwidth efficiency, hence its throughput As has been discussed in the Introduction, to apply the dual feedback algorithm for calculating the granted service rate s(n), the corresponding granted bandwidth b(n) has to be a function of time (6) Replacing B(z) in (5) using (6) gives us the resulting discrete-time transfer function of the dual feedback mechanism G( z) = Eq ( z ) A( z ) − z −1 = Ta − z (1 − αCr ) + (αK q + αCr − 2) z −1 + (7) The stability of the discrete-time system in (7) requires that poles of G(z) are located within the unit circle It can be easily verified that this requirement is satisfied if 0< αCr