A Cross-Layer Framework for Efficient Packet Scheduling in ...

A Cross-Layer Framework for Efficient Packet Scheduling in Wireless CDMA Networks Saied M. Abd El-atty, Dimitrios N. Skoutas, Angelos N. Rouskas Department of Information and Communication Systems Engineering, University of the Aegean, Samos 83200, Greece {ssoliman, d.skoutas, arouskas}@aegean.gr

Contact details of the first author:

Saied M. Abd El-atty Soliman Department of Information and Communication Systems Engineering University of Aegean Karlovassi 83200 Samos, Greece. Tel.: +30227 3082261 Fax.: +30227 3082009 Email: [email protected] Abstract In this paper we present a cross-layer framework for efficient packet scheduling in wireless CDMA networks. At the Medium Access Control layer, we perform a prediction of the future state of the wireless channel for each user by utilizing information from the physical layer. According to this prediction we define which users should be served by the packet scheduler during the next frame. The employed Delay Fair Scheduler (DFS) provides QoS differentiation according to the delay sensitivity of each service. The efficiency of the proposed scheme, in terms of average packet delay, throughput and channel utilization is verified via simulation.

Keywords CDMA, Cross-Layer Framework, FSMC, Quality of Service, Packet Scheduling.

A Cross-Layer Framework for Efficient Packet Scheduling in Wireless CDMA Networks Saied M.Abd El-atty, Dimitrios N. Skoutas and Angelos N. Rouskas Department of Information and Communication Systems Engineering, University of the Aegean, Samos 83200, Greece {ssoliman, d.skoutas, arouskas}@aegean.gr Abstract- In this paper we present a cross-layer framework for efficient packet scheduling in wireless CDMA networks. At the Medium Access Control layer, we perform a prediction of the future state of the wireless channel for each user by utilizing information from the physical layer. According to this prediction we define which users should be served by the packet scheduler during the next frame. The employed Delay Fair Scheduler (DFS) provides QoS differentiation according to the delay sensitivity of each service. The efficiency of the proposed scheme, in terms of average packet delay, throughput and channel utilization is verified via simulation. Keywords- CDMA, Cross-Layer Framework, FSMC, Quality of Service, Packet Scheduling.

wireless channel in the scheduling procedure and thus they are not so efficient in allocating the available bandwidth to the users. In this paper we introduce a cross-layer technique (CROT) which tries to predict the future state of the wireless channel of each user in order to make the packet scheduling procedure more efficient. For the prediction of the future state of the wireless channel, we model it with a Finite State Markov Chain (FSMC) [7], based on SINR measurements of the received signal at each mobile. According to this prediction we define which users should be excluded from service during the next frame. The rest of the users are served according to the Delay Fair Scheduler [8] scheme.

I. INTRODUCTION The designing of modern networks is in general based on a layered architecture. Each layer is associated with specific functions and communicates with other layers through a particular interface. The obvious advantage of this technique is that each layer can be redesigned without affecting the rest of the layers as long as it keeps the same interface. However the layered architecture can also redirect the network designer, leading him to isolate the functions of each layer from essential data coming from other layers. In the past few years, many research works on wireless systems were concentrated on optimizing a single layer in the protocol stack [1]. Furthermore, it is well known that the lack of correlation between network layers often causes the deterioration of the network throughput [2]. Since in each layer the QoS is defined in different terms the coordination between layers is essential in order to preserve the desired QoS. For example at the physical layer, QoS is synonymous to the acceptable bit error rate (BER) or to the signal to interference and noise ratio (SINR), while at the Medium Access Control (MAC) layer, QoS is usually defined in terms of minimum rate or maximum delay guarantees [3]. Many scheduling schemes employed at the MAC layer have been proposed for wireless networks [4, 5, and 6]. Most of these schemes do not take into account the state of the

The paper is organized as follows. In Section II, we present the proposed cross-layer framework. In Section III, the prediction criterion is presented. Finally, in Section IV, we describe the simulation model and we evaluate the performance of the proposed scheme. II. SYSTEM MODEL The concept of our proposed scheme is presented at Fig. 1. A. Medium Access Control (MAC) Layer At the MAC layer the SINR information gathered from the physical layer is utilized by the packet scheduling procedure. Prediction Criterion Each connection i has its own QoS requirements in Bit Error Rate and therefore a BER threshold, BERT arg et , is defined. The i BER is related to the SINR of the received signal at the mobile. For each connection i two SINR thresholds are also defined: Therefore, according to the SINRmini and SINRT arg eti . measured SINRi : a)

If SINRi ≥ SINRT arg et then BERi ≥ BERT arg et and the i i

QoS requirement is satisfied. b) If SINRi < SINRmin then BERi < BERT arg et and the QoS i i requirement is not satisfied.

Fig. 2. FSMC for wireless Rayleigh fading channel.

where Di (nTs ) is the head-of-line packet delay for queue i, Ts=10ms is the scheduling period of the DFS scheme and D th is the packet delay threshold. The delay of data i

packets must be kept below this threshold in order to preserve the desired QoS. Pi is recalculated at the start of each frame. b) In the second part, the rate assignment to the connections is performed depending on their priority and the available capacity of the system. c) In the third part, the assignment of the OVSF (Orthogonal Variable Spreading factor) channelization codes to the connections is performed.

Fig.1. Cross-Layer Framework.

c)

Finally the last case occurs if . This case needs further SINRmini ≤ SINRi < SINRT argeti investigation with the prediction criterion in order to determine if the required BER can be achieved.

For the last case a Finite State Markov Chain (FSMC) is defined. The FSMC model, shown in Fig. 2, represents the time varying behavior of the Rayleigh fading channel [7]. By using this model, which is described in detail in the following section, we are able to make a more accurate prediction of the future state of the wireless channel. Based on this prediction we decide which users will be served by the packet scheduler.

B. Physical Layer Finally, each user’s data are transmitted through the time varying, multi-path fading channel. The SINR value of the received signal is measured at the mobile and transmitted back to the base station. Subsequently the SINR information is passed to the MAC layer in order to calculate the prediction criterion for the next frame. C. Step by step description of the proposed Cross layer technique A step by step description of the proposed Cross-Layer Technique (CROT) follows. Connections with empty queues are excluded from the next steps. At the start of each frame: 1) FOR each active connection excluding connections with empty queues: a) Measure the received SINRi for each connection i. 2) Compare SINRi with SINRmin and SINRT arg et . i

Delay Fair Scheduler The users which pass the prediction criterion are served by the Delay Fair Scheduler [8]. The DFS scheme consists of three basic parts: a)

In the first part, the priority Pi for each connection is calculated. The priority Pi is defined by the following equation: D (nT ) Pi = i s ≥ 0, n =0,1,2,... (1) Dth i

i

a) IF SINRi < SINRmin then user i is excluded from the i next steps. b) IF SINRi ≥ SINRT arg et then user i will be served by the i c)

DFS scheduler. IF SINRi lies in the interval SINRmin ≤ SINRi < SINRT arget , i i then the prediction criterion is used. User i will be served by the DFS scheduler only if his predicted error probability is above the respective target error probability.

3) Delay Fair Scheduler a)

between in-adjacent states is very small, so it can be assumed that transitions happen only between adjacent states.

All the qualified connections from the previous steps are served by the DFS scheduler.

III. PREDICTION CRITERION BASED ON THE FSMC MODEL The prediction criterion consists of three parts. At the first part we define the parameters of the FSMC model of the user according to the SINR measurements at the previous frame. In the sequel, we calculate the most probable state of the wireless channel for the next frame. Finally, for the predicted state of the wireless channel we calculate the respective error probability and we decide if the user should be served by the scheduler according to his QoS requirements. A. Parameters of the FSMC model The parameters of FSMC model in Fig. 2 are obtained by partitioning the received SINRi of user i into K states. Let ψi be the instantaneously received SINRi of user i in the multipath fading environment, which is proportional to the square of the signal envelop. The probability density function (pdf) of ψi can be expressed as in [9]. 1 −ψ i /ψ 0 , p(ψ i ) = e ψi ≥ 0 (2)

ψ0

where ψ0 =Ε{ψi} is the average value of SINR. Suppose that Ψ0=0