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Improving Throughput and Fairness on the Downlink Shared Channel in UMTS WCDMA Networks Shahzad Ali Malik and Djamal Zeghlache Telecommunication Networks and Services Department Institut National des Telecommunications 9, rue Charles Fourier, 91011 Evry Cedex, France Tel: (+33) 1 60 76 45 84, Fax: (+33) 1 60 76 42 91 [email protected], [email protected]

ABSTRACT A resource scheduling scheme is presented to improve throughput and fairness for NRT packet data traffic on the downlink shared channel of a UMTS WCDMA network supporting multiple services. The proposed Fair Resource Scheduling (FRS) scheme takes into account link conditions to enhance throughput and provides fair resource sharing among traffic flows. FRS includes service priority handling during admission and scheduling to provide service class differentiation. The scheduling disciplines presented in this paper aim at improving throughput and delay performance of packet users while ensuring fair service to all admitted users. The analysis indicates that a fair resource scheduling policy provides the required throughput and delay performance for packet data over the WCDMA downlink. I.

INTRODUCTION

An efficient radio resource management is vital to support multimedia services with diverse QoS requirements over the radio interface. For 3G mobile networks such as the UMTS WCDMA, advanced and specific radio resource control is required to fulfill the expected performance from theses systems. Various resource management algorithms such as connection admission control, load control and packet scheduling need to be improved to properly handle multiple services and maximize resource utilization. For the UMTS WCDMA downlink, efficient packet scheduling can be used to manage the non-real-time traffic flows to meet QoS targets. A scheduling scheme, when carefully selected, can achieve higher throughput and fairness and bring about the needed performance improvements. The issue of fair packet scheduling has been intensively studied and solutions have been proposed following the weighted fair queuing paradigm, presented in [1,2]. In recent years research efforts focussed on adapting fair scheduling to wireless cellular networks to handle the highly unpredictable wireless propagation environment characterized by location-dependent bursty error behavior

[3, 4]. This paper analyzes fair scheduling over shared channels in UMTS mobile cellular networks. In UMTS WCDMA networks, a downlink shared channel has been specified to accommodate NRT services with flexible QoS requirements. To meet minimum QoS levels for the various traffic flows on the DSCH, efficient and fair scheduling is required. A scheduling scheme for the DSCH is proposed to handle traffic flows according to their service class priority, taking into account the channel status information while ensuring fairness among the backlogged traffic flows. This scheme is compared with simple round robin (RR) and link status aware (LSA) schemes to highlight the achieved benefits. The objective of the prioritized and channel state dependent fair resource control mechanism proposed in this paper is to provide some insight into differentiated resource management applied to the WCDMA downlink. Section II of this paper describes briefly the downlink shared channel (DSCH) of UMTS WCDMA System. Scheduling and fairness issues are discussed in the Section III. Section IV outlines the simulation model, study scenarios and performance metrics. Results are presented and commented in Section V while Section VI concludes this work. II.

UMTS DOWNLINK SHARED CHANNEL

In UMTS WCDMA downlink, the base station has a limited transmission power budget and a limited number of orthogonal channelization codes available. Proper management of these two crucial resources is extremely important. Typically, the user data is transmitted on dedicated channels (DCHs). Each DCH has its own specific OVSF code corresponding to an appropriate spreading factor (SF) normally assigned for the whole duration of the connection. However, if the number of users requiring DCHs becomes large, particularly at low spreading factors, the code shortage could result in blocking some of the users. For packet data users with bursty traffic, the assignment of a DCH for the whole duration of the session results in wasteful utilization of the resource, degrades system performance and increases blocking. A better approach to overcome this code

shortage problem is to assign the same code channel to several packet data users and exploit the bursty characteristics of traffic to efficiently service these users. Consequently, a downlink shared channel (DSCH) has been specified for WCDMA by 3GPP [5].

users with bad channel conditions is deferred but users are compensated later when their channel conditions improve. Achieving such resource allocation calls for some sort of fair scheduling and requires taking into consideration the radio environment.

For NRT services with tolerable delay requirements, the DSCH provides an efficient transmission mode for sharing power and code resources, overcomes the channelization code shortage and enhances system capacity and performance. Several users belonging to NRT service classes share the same physical channel (i.e. the same OVSF code) through time division scheduling. The scheduling may be carried out at the single frame level (10 ms) or over several frames. Thus DSCH enables multiple data users with relatively low activity and bursty traffic to share a high data rate channel employing a single channelization code at low spreading factor. Users on a DSCH can not benefit from macro-diversity. Only one base station transmits data on the shared channel.

A priority oriented scheduling scheme, called the Fair Resource Scheduling (FRS), based on Round Robin scheduling enhanced with flow priority, link conditions and fairness among the various flows, is proposed. The fair resource scheduling (FRS) scheme includes the following:

III.

SCHEDULING AND FAIRNESS

On the downlink shared channel (DSCH), the base station transmits to several different users in its cell area. Each user has a different link or channel condition depending upon its location and interference from other cells. Admitted users are transferred to the scheduling queue and allocated a dedicated control channel for signaling and control purposes. Active connections, in the scheduling queue, are served on the basis of a scheduling policy. The scheduling discipline is used to determine which user will be allowed to transmit in the next transmit interval. The choice of a scheduling strategy influences the overall behavior of the system, particularly in a multiple service. Basically, there are two resources to be managed on the downlink shared channel (DSCH). Namely, the transmit power budget for the packet channels and the scheduler time (e.g., the amount of time or the number of radio frames allocated to a certain flow). If all the users have error free channels or links, the assigned percentage of bandwidth would correspond to the percentage of time the scheduler allocates to each user. A simple Round Robin policy could be employed to ensure every user its due share of scheduling time or bandwidth. In reality, radio channels are time varying because of fading and interference. Traffic flows experience different propagation conditions due to their spatial position, mobility and temporal variations of the radio propagation environment. Although users are sharing the radio channel, the radio link state for each user is independent because each user is subject to different and independent fading and interference conditions. Allocating all the available radio resources to users experiencing best radio channel conditions can maximize system throughput. Service for

•

a mechanism to take into account the radio link conditions for the various traffic flows on the DSCH

•

a fairness mechanism to ensure some degree of fair access to backlogged flows

•

prioritization to handle multiple service classes on a single DSCH

•

an individual traffic channel power limit for each flow and a total BS transmit power budget threshold For the Fair Resource Scheduler, the priority-based queues are sequentially examined to determine from which flow the next packet is to be transmitted or while taking into consideration the channel status. The fairness mechanism is based on Weighted Fair Queuing (WFQ) where each flow has a weight. The weight determines the percentage of available resource allocated to a given flow. On the basis of their actual achieved transfer bit rate, the flows are marked as leading, lagging or in-synch with their required bit rate. Over an appropriate period of time, the flow states are updated and currently experienced leads or lags are calculated. The lagging flows are compensated through allocation of additional scheduling time over the scheduling cycle if link conditions have improved for such flows. Resource allocation is thus controlled and managed through this weighted scheduling to achieve fairness for backlogged flows. The fairness mechanism aims at providing each flow its allocated percentage of the effective throughput defined as the total throughput achieved at each instant. This requires estimation of the bandwidth used by each flow over the appropriate time interval to determine whether or not a flow has been receiving its required share of the resource. Any excess bandwidth should also be distributed in a fair way. Leading or in-synch flows are permitted to transmit even if there exist other lagging flows, provided the particular flow has a good link and all unsatisfied or lagging flows have bad links. This avoids the loss of throughput and the waste of resources. The priority oriented fairness feature of the proposed FRS scheduling is also important in providing

differentiated services in UMTS WCDMA networks. Through priority, different traffic flows can be isolated while sharing the same radio resource. IV.

SIMULATION MODEL

This performance analysis has been conducted using an event driven dynamic UMTS WCDMA network simulation model, developed in OPNET network modeling tool [8]. Simulation parameters used in this study are provided in Table 1. Environment scenario and various models employed in the simulation follow ETSI SMG2 recommendations and procedures [6, 7]. A multiple cell environment consisting of small macro cells (omnidirectional coverage) is considered. Cell selection by mobile station is achieved through minimum path loss criterion. The simulation time is slot (0.67 ms) and frame based (10 ms). Fast closed loop power control resolution corresponds to smaller steps where SIR calculations and power updates can be performed. RT conversational and streaming services are represented by a CBR flow with 100% activity in circuit switched mode over dedicated channels. A WWW model described in [6] is used for the NRT interactive service class and background traffic is poisson with exponential inter-arrivals. TABLE 1: SIMULATION PARAMETERS Simulation Parameter

Value

Radio access Chip rate Deployment scheme Cell radius User speed (Uniform Distribution) Distance loss exponent Log normal shadowing Soft handover margin

WCDMA (FDD Downlink) 3.84 Mcps Hexagonal (omni antennas) 500 meters 0-60 Km/h 4 Mean: 0 dB, Std: 10 dB 3 dB ΠReal Time: 2 ΠNon Real Time: 1 43 dBm

Max. active set size Max BS power Common channels + Voice service power Max. traffic channel power Power control range Power control step size Orthogonality factor γ Dedicated channel rates (Inf. bits) Shared channel rate (Inf. bits) User bit rates Service classes Service activity factor

Eb/No target

33 dBm 30 dBm 25 dB 1 dB (400 Hz) 0.4 64, 128 Kbps 384 Kbps Variable, 384 Kbps Max Conversational, Streaming Interactive, Background Conversation and Streaming: 100% ΠR T 64 Kbps: 2.5 dB ΠRT 128 Kbps: 2.0 dB ΠNRT : 2.0 dB

The performance in terms of active session throughput [Kbps] and the mean SPDU delay [sec], neglecting the influence from higher layer protocols is reported as the

focus of this work is on supporting interactive and background services. The active session throughput is defined as the ratio of correctly received user bits during the entire session and the session length, excluding the time where there is nothing to transmit. The base station (BS) transmit power in dBs is also evaluated. The DSCH considered in this work is a fixed rate channel at a spreading factor of 4. All users sharing the DSCH have an associated DCH at a spreading factor of 256 for control and signaling information transmission. A single traffic flow can achieve a maximum throughput of 384 Kbps if the channel is error free and allocated entirely to this flow. V.

SIMULATION RESULTS

Performance analysis of fair resource scheduling has been conducted through extensive simulations using a dynamic event driven UMTS WCDMA simulator. Simple round robin (RR) and link status aware (LSA) scheduling schemes have also been evaluated for comparative purposes. Two different study scenarios have been considered for this work. For each study scenario, the performance evaluation is carried out for the following scheduling schemes: •

Round Robin (RR)

•

Link Status Aware (LSA)

•

Fair Resource Scheduling (FRS)

The first study scenario consists of four packet data flows belonging to interactive service class. All the four flows have equal priorities for resource allocation and are assigned the same weights so that each one will have the same share of the scheduler time resource. Fig. 1 through Fig. 4 depict the achieved throughput and delay performance and Fig. 5 reports the base station transmit power for this scenario. Fig. 1 through Fig. 3 represent the active session throughput achieved for each flow for the three scheduling schemes, simple Round Robin (RR) scheduling, Link Status Aware (LSA) and the fair resource scheduling (FRS) respectively. It is observed that the FRS scheme ensures fairness among multiple flows in addition to significant improvement in throughput as compared to RR scheduling. The LSA scheme although improves throughput considerably over RR but results in unequal resource sharing among the flows as it lacks any mechanism to provide fair resource access. As can be seen from Fig. 1 that each of the four traffic flows achieves a different level of throughput depending on the respective link conditions. For instance, for 80% of the time, flow 1 and flow 2 achieve throughputs of 85 Kbps and 90 Kbps respectively while flow 3 and flow 4 attain about 100 Kbps. However, achieved throughput remains less than

100 Kbps for all flow, with throughput values varying in the range between 80Kbps and 100Kbps.

RR

CDF

Flow 3

Flow 2 Flow 4 Flow 1

While for the LSA and FRS schemes as shown in Fig. 2 and Fig. 3, there is more than 20% increase in throughput for all flows which clearly demonstrates the benefit gained from link status information being taken into consideration at the time of scheduling packet for a particular flow. However, the LSA scheme although achieves significant improvement in throughput but does not provide fair resource share to the flows. The FRS scheme, on the other hand, guarantees fairness among the traffic flow while achieving comparable improvement in throughput also as depicted in Fig. 3 where each of the four flows achieves a throughput of about 120 Kbps.

FRS

Throughput (Kbps)

LSA CDF

Fig. 1: CDF of Throughput – Round Robin Scheduling

RR

LSA Flow 3

CDF

Flow 4

Flow 2

SPDU Delay (s)

Fig. 4: CDF of Mean SPDU Delay for Traffic Flows Flow 1

LSA CDF

FRS

Throughput (Kbps)

RR

Fig. 2: CDF of Throughput – Link State Aware Scheduling

FRS

Flow 3 Flow 2

CDF

BS Transmit Power (dBs)

Fig. 5: CDF of BS Transmit Power

Flow 1 Flow 4

Throughput (Kbps) Fig. 3: CDF of Throughput –Fair Resource Scheduling

The CDF of mean SPDU delay shown in Fig.4 demonstrates the gain in delay performance for the traffic flows. It can be seen that about 95% of SPDUs experience a delay of 2 seconds or less for the FRS strategy while for CSA and RR schemes, the percentage of SPDUs experiencing delay of 2 seconds or less is about 88% and 70% respectively. Additionally, FRS also provides an improvement in power resource utilization as it results in

The second study scenario consists of four packet data flows, two belonging to interactive service class and the other two to the background class. Interactive class flows have higher priority over the background class flows for resource allocation. Flows within each priority group are assigned the same weights. This means that background flows will share equally the remaining available resource once the higher priority interactive flows have been serviced.

prioritization among flows provides a flexibility in achieving specific service class oriented QoS objectives.

Flow 3

Flow 4

Flow 2

Flow 1

CDF

relatively smaller BS transmit power being consumed in comparison to RR and CSA schemes as shown in Fig. 5.

FRS

The achieved throughput and delay performance for the second scenario are reported in Fig. 6 through Fig. 10 while Fig. 11 shows the base station transmit power for this scenario.

Throughput (Kbps)

RR

CDF

Fig. 8: CDF of Throughput –Fair Resource Scheduling

Flow 3 Flow 2

Flow 1 Flow 4

Throughput (Kbps)

Fig. 6: CDF of Throughput – Round Robin Scheduling

It is observed in this priority distinctive scenario, the FRS scheme performs equally well in achieving both fairness and throughput improvement for the multiple flows in each priority class. Both interactive class and background class flows achieve higher throughput as compared to RR scheduling. The interactive class flows achieve a throughput of about 150 Kbps that is much higher than that achieved in first scenario. However this increase in throughput for interactive flows is at the cost of background flows. This demonstrating the flexibility offered by this approach in managing scarce resources to meet specific QoS levels for higher priority service classes. While the throughput for FRS scheme is comparable in comparison to the LSA scheme, however a fair resource allocation among the flows is attained.

LSA

Flow 2

FRS

CDF

Flow 4

LSA

CDF

Flow 3

RR

Flow 1

Throughput (Kbps)

Fig. 7: CDF of Throughput – Link State Aware Scheduling

Fig. 6 through Fig. 8 depict the active session throughput achieved for each of the interactive and background flows for the three scheduling schemes, simple Round Robin (RR), Link Status Aware (LSA) and the Fair Resource Scheduling (FRS) respectively. It is evident that

SPDU Delay (s)

Fig. 9: CDF of Mean SPDU Delay for Interactive Traffic Flows

performance of packet users while ensuring fair service to all admitted users and resulting in better overall system performance. This scheduling discipline incorporates mechanisms to take into account the link conditions for each flow, ensure fairness and provide differentiated treatment to flows based on service class priority.

FRS LSA

CDF

RR

SPDU Delay (s)

Fig. 10: CDF of Mean SPDU Delay for Background Traffic Flows

The CDF of mean SPDU delay experienced by traffic flows for the three scheduling schemes as depicted in Fig. 9 and Fig. 10 are in conformity with earlier results. It can be seen that delay performance considerably improves for both the interactive and background flows. As can be observed from Fig. 9 that the mean delay experienced by more than 95% SPDUs belonging to interactive flows remains below 2 seconds for the FRS scheme while this reaches to about 5 seconds and 6 seconds for LSA and RR schemes respectively. Similarly, for the background flows, the mean delay experienced by the SPDUs if 5 seconds for the FRS scheme and about 10 seconds for both RR and LSA schemes.

The reported results manifest that the proposed fair resource scheduling achieves the twin goals of improving throughput and ensuring fairness among the packet flows while resulting in an optimal resource utilization. The differentiated traffic handling policy permits a greater flexibility in controlling and managing resources efficiently. A prioritization among the NRT services enables to offer packet services with varying degrees of QoS guarantees. Certain applications or users may obtain assured service with a predefined quality level while providing the best effort service to remaining applications or users. The significant decrease in the base station transmit power for the proposed scheduling scheme as compared to simple round robin or link status aware scheduling schemes translates into additional capacity as transmit power is the most crucial resource in CDMA systems. Although a lot of effort is being devoted to enhancing WCDMA system capacity through introduction of various new radio technologies, optimizing resource management techniques is equally vital in providing services with diverse QoS requirements, ensuring optimum resource utilization and achieving higher capacity. REFERENCES A. K. Parekh and R. G. Gallager, “A generalized processor sharing approach to flow control in integrated services networks: the single node case”, IEEE/ACM Transactions on Networking, vol. 1, no. 3, pp. 344-357, June 1993.

[2]

A. Demers, S. Keshav and S. Shenker, “Analysis and simulation of a fair queuing algorithm”, ACM SIGCOMM’89, pp. 1-12, August 1989.

[3]

V. Bharghavan, S. Lu and T. Nandagopal, “Fair queuing in wireless wetworks : issues and approaches”, IEEE Personal Communication, pp. 44-53, February1999.

[4]

T. S. Ng, I. Stoica and H. Zhang, “Packet fair queuing algorithms for wireless networks with location dependent errors”, IEEE INFOCOM’98, pp. 1103-1111, March 1998

[5]

3GPP TS 25.211 UMTS: Physical channels and mapping of transport channels onto physical channels (FDD), V 3.4.0 Release 1999.

[6]

ETSI Technical Report 101 112, “Selection procedures for the choice of radio transmission technologies of the UMTS”, UMTS TR 30.03

[7]

ETSI/SMG;, “Evaluation Report for ETSI UMTS Terrestrial Radio Access (UTRA)”, ITU-R RTT Candidate Submission, Tdoc SMG2 260/98.

[8]

OPNET Modeler/ Radio, MIL3 Inc., 3400 International Drive, Washington, DC, USA.

LSA

CDF

FRS

[1]

RR

BS Transmit Power (dBs)

Fig. 11: CDF of BS Transmit Power

Similar to the first scenario, there is a significant decrease in BS transmit power in case of FRS as compared to RR and LSA schemes as shown in Fig. 11. This demonstrates that respective QoS requirements can be met for specific services through prioritization, while attempting to achieve optimal overall system performance. VI.

CONCLUSIONS

A fair resource scheduling discipline has been presented that may be employed to improve throughput and delay