Performance Evaluation of Bandwidth and QoS Aware LTE Uplink ...

Performance Evaluation of Bandwidth and QoS Aware LTE Uplink Scheduler Safdar Nawaz Khan Marwat, Yasir Zaki, Carmelita Goerg ComNets, University of Bremen, 28359 Bremen, Germany {safdar, yzaki, cg}@comnets.uni-bremen.de Thushara Weerawardane, Andreas Timm-Giel ComNets, Hamburg University of Technology, 21073 Hamburg, Germany {tlw,timm-giel}@tuhh.de

Abstract. A Long Term Evolution (LTE) eNodeB Medium Access Control (MAC) uplink scheduler is proposed in this paper for Single Carrier Frequency Division Multiple Access (SC-FDMA) as the uplink transmission scheme. Uplink scheduling algorithms available in literature commonly do not consider all the essential features of the LTE uplink. The proposed scheduler is shown to provide efficient allocation of radio resources to User Equipments (UEs) according to Quality of Service (QoS) of various traffic classes and the instantaneous channel conditions. The scheduler functionality is divided into Time Domain Packet Scheduling (TDPS) and Frequency Domain Packet Scheduling (FDPS). The proposed scheduler also supports multi-bearer UEs. The performance of the proposed scheduler is compared with common TDPS schedulers like Blind Equal Throughput (BET), Maximum Throughput (MT) and Proportional Fair (PF). The results show that the proposed scheduler guarantees provision of QoS to UEs and achieves an acceptable performance in terms of throughput. Keywords: SC-FDMA, uplink, scheduling, bandwidth, QoS;

1

Introduction

Single Carrier Frequency Division Multiple Access (SC-FDMA) in Long Term Evolution (LTE) uplink divides the transmission bandwidth into subcarriers to provide resource allocation flexibility and to achieve high spectral efficiency. The User Equipment (UE) consumes low battery power due to low Peak-to-Average Power Ratio (PAPR) of the SC-FDMA signals. A major SC-FDMA constraint is that the subcarriers allocated to a single UE should to be adjacent to each other. Designing a packet scheduler requires tackling of various conflicting requirements such as channel conditions, fairness, throughput, delay etc. The scheduler should be aware of the number of maximum Physical Resource Blocks (PRBs) allocable to a UE determined by Power Control (PC). The scheduler should support multi-class UEs. The resources should be allocated to UEs according to UE buffer size. adfa, p. 1, 2011. © Springer-Verlag Berlin Heidelberg 2011

Literature survey shows that most of the research work in this field is directed towards downlink scheduling [1,2] etc. Subcarrier allocation algorithm proposed in [3] is search-tree based with fixed size and contiguous bandwidth allocation. This algorithm does not utilize the bandwidth flexibility feature of SC-FDMA. Adaptive transmission bandwidth algorithms in [4,5] provides better throughput performance but other uplink scheduling aspects (e.g. QoS provision) are not addressed. Throughput based QoS metric is proposed in [6] for optimizing resource utilization and fairness but multi-bearer UE support is not addressed. [7] suggests the number of UEs to be scheduled in a Transmission Time Interval (TTI) be adjusted according to Transmission Control Protocol (TCP) congestion window size but QoS provision and other scheduling aspects are not discussed. The weighted metrics based on path loss [8] and intercell interference [9,10] can improve the cell throughput, but QoS fulfillment cannot be ensured. Throughput based QoS weight is introduced in [11] but it cannot serve delay sensitive traffic efficiently. Most of the work on the topic does not consider the PC functionality.

2

Bandwidth and QoS Aware Uplink Scheduler

This paper presents Bandwidth and QoS Aware (BQA) LTE uplink scheduler, which encapsulates most of the features of SC-FDMA based LTE uplink in its functionalities by combining the bits-and-pieces of the research work previously done on the topic. The BQA scheduler is optimized to guarantee QoS provision to the UEs within the maximum number of allowed PRBs (tuned by Fractional Power Control (FPC) scheme based on Closed Loop Power Control (CLPC) [12]). It maximizes the cell throughput by giving priority to UEs with better channel conditions and maintains some level of fairness by providing resources to UEs with adverse channel conditions. Multiple QoS traffic type UEs are also supported by the scheduler, which is the missing aspect of most of the schedulers proposed in literature. The scheduling is performed in two main phases i.e. the Time Domain Packet Scheduling (TDPS) and the Frequency Domain Packet Scheduling (FDPS). 2.1

Time Domain Packet Scheduling

The TDPS phase is designed to prioritize scheduling candidate UEs for a particular TTI in a given cell. A candidate gets high metric value if it has stringent QoS requirements, better channel conditions and/or has been unable to obtain any significant resources in the recent past TTIs. The presence of data packets in the buffer of a UE is reported to the eNodeB using Buffer Status Reports (BSRs). The channel condition of the active UEs (having pending uplink data) is acquired using Channel State Information (CSI) carried by Sounding Reference Signals (SRSs). In this work, it is assumed that the SRSs are received at the eNodeB in each TTI for all the PRBs of active UEs; and the eNodeB is aware of the Power Spectral Density (PSD) of each active UE using power headroom reports. The TDPS metric values are generated for each active UE by using algorithm named as 'weighted Proportional Fair' (wPF) algo-

rithm. The metric value is based on QoS weight and channel conditions of UEs along with fairness. The QoS weight of a UE depends on throughput and delay requirements of its radio bearers. The TDPS metric value for UE 𝑖 is formulated as: 𝑅!"#$,! 𝑡, 𝑛! 𝛬! (𝑡) = 𝑊!,! (𝑡) (3) 𝑅!"#,! 𝑡 !

Where 𝛬! (𝑡) is the TDPS metric value for UE 𝑖, 𝑅!"#$,! 𝑡, 𝑛! is the instantaneously achievable throughput of UE 𝑖 having maximum allowed number of PRBs 𝑛! (set by FPC), 𝑅!"#,! (𝑡) is the average throughput of UE 𝑖 at time 𝑡 expressed as in (4), 𝑊!,! (𝑡) is the QoS weight of the bearer 𝑘 of UE 𝑖 at time 𝑡 and expressed as in (5): 1 1 (4) 𝑅!"#,! (𝑡) = 1 − 𝑅 𝑡 − 1 + 𝑅!"!,! (𝑡) Τ !"#,! 𝛵 Where 𝛵 is the Exponential Moving Average (EMA) time window and 𝑅!"!,! (𝑡) is the actual bit rate achieved by UE 𝑖 in previous TTI. 𝑅!"#,! 𝜏!,! 𝑡 𝑊!,! 𝑡 = . . 𝜚 (𝑡) (5) 𝑅!"#,!,! 𝑡 𝜏!"#,! ! Here, 𝑅!"#,! is the bit rate budget (minimum throughput) and 𝜏!"#,! is the end-toend delay budget of QoS class 𝑘, 𝑅!"#,!,! 𝑡 is the average throughput and 𝜏!,! (𝑡) is the average delay of bearer 𝑘 of UE 𝑖, 𝜚! (𝑡) is a variable with value set to 10 if 𝜏!,! (𝑡) is above the threshold value of bearer 𝑘 at time 𝑡, otherwise equal to 1. A list of bit rate budget, packet delay budget and delay threshold values for various QoS classes (defined according to their traffic models) is given in TABLE I. TABLE I: BEARER BIT RATE BUDGET; DELAY BUDGET AND DELAY THRESHOLD Traffic

Bit rate budget

Packet end-to-end

Packet delay

Type

(Kbps)

delay budget (ms)

threshold (ms)

VoIP

55

0.1

0.02

Video

132

0.3

0.1

HTTP

120

0.3

--

FTP

10

0.3

--

Figure 1: M RCs with chunk size 3 and bandwidth of N PRBs

2.2

Frequency Domain Packet Scheduling

In FDPS, a certain number of high priority UEs are selected for allocation of frequency resources within the TTI. The bandwidth is divided into portions (Fig. 1) called Resource Chunks (RCs). The RCs are allocated to the chosen UEs based on the

FDPS metric values for each RC of each UE and the maximum RCs allowed to each UE (set by FPC). The FDPS metric values also consider the criteria of QoS assurance, throughput maximization and fairness. The allocation of resources is achieved by using a search-tree based algorithm. The bearers of UE with multiple QoS traffic types are scheduled according to their QoS requirements. In FDPS, a certain number of UEs with highest TDPS metric values are selected for scheduling. The ‘Proportional Fair Scheduled QoS-aware’ (PFSchedQ) FDPS metric is introduced. The FDPS metric value for a PRB 𝑐 is expressed as follows: 𝑅!"#$,!,! 𝑡 𝜆!,! (𝑡) = . 𝑊!,! (𝑡) (6) 𝑅!"!,!"#,! 𝑡 !

Where 𝜆!,! (𝑡) is the FDPS metric value for PRB 𝑐 of UE 𝑖, 𝑅!"#$,!,! 𝑡 is the instantaneously achievable throughput for PRB 𝑐 of UE 𝑖, 𝑅!"!,!"#,! (𝑡) is the instantaneously achievable throughput of UE 𝑖 over only those TTIs where 𝑖 successfully enters the FDPS. PRB Allocation Algorithm The ‘Fixed Size Chunk and Flexible Bandwidth’ (FSCFB) algorithm is proposed for PRB allocation to UEs. This algorithm divides the spectrum into several RCs. Variable number of RCs can be allocated to UEs. All possible RC allocation combinations are checked in order to find the best one. The algorithm is computationally intense and therefore, the resolution of this algorithm in frequency domain has been reduced to RC level (and not PRB level). The combinations not following the restrictions of contiguity, buffer size, and maximum allowed PRBs are discarded, resulting in reduced complexity. The steps involved in this algorithm are summarized as follows: 1. 2.

3. 4.

Make a UE-RC table (Figure 2) with each element being the RC metric value of the UE, i.e. the sum of PRB metric values within that RC. Make all possible combinations of UE-RC allocation using search-tree algorithm (explained later) while respecting the contiguity, buffer size and maximum allowed PRBs constraint; and determine the resulting global metric value for each combination. Choose the combination with the best global metric value. Obtain the resource allocation from best combination. RC0

RC1

RC2

UE0

10

6

3

UE1

11

10

5

Figure 2: A sample UE-RC table for two UEs and three RCs

Step 2 utilizes a search-tree based resource allocation algorithm named as ‘unique Depth-First Search’ (uDFS) algorithm with contiguity, buffer size and maximum allowed PRBs constraints. The uDFS checks all possible combinations of RC allocation. The combinations which do not follow the constraints are discarded and further depth of that node is not explored. In Figure 3, it is assumed that at most, 2 RCs can

be allocated to a UE. The blue nodes breach contiguity constraint and the red nodes breach maximum PRBs constraint.

Figure 3: uDFS tree for two UEs and three RCs

UE Bearer Service In multi-bearer UE scenario, the allocated bandwidth is further subdivided among the UE bearers. Each UE bearer has its own QoS requirements related to delay budget, rate budget and delay threshold. The UE has to feed its bearers in efficient manner to ensure QoS provision and to avoid bearer starvation. The method proposed for bearer service is named as “weighted service”. In this method, a bearer is served according to its QoS weights, 𝑊!,! 𝑡 without any priority to GBR. However, the bearers having reached their packet delay threshold are given strict priority and the available resources are allocated to them before serving other bearers.

3

Simulation Results and Analysis

The QoS and the throughput performance of BQA scheduler is compared with commonly used TDPS schedulers; the Blind Equal Throughput (BET), the Maximum Throughput (MT) and the Proportional Fair (PF). In FDPS, these schedulers are combined with the Proportional Fair Scheduled (PFSched). All the schedulers in the simulations avail the FSCFB algorithm and therefore, show performance mostly comparable to the proposed scheduler. The reference schedulers serve the UE bearers by giving strict priority to GBR bearers. TABLE II gives the simulation parameters used. VoIP, FTP and Video Single-Bearer UEs Scenario In this scenario, the BQA scheduler and the reference schedulers (BET, MT and PF) are compared with 8 FTP UEs initially. The traffic is modified for successive simulations by adding 2 VoIP UEs and 2 video UEs step-wise. So the simulations are performed for 8 FTP UEs with 0, 2, 4, 6, 8 and 10 VoIP/video UEs respectively. The average cell throughput and FTP response time results are depicted in Figure 4 and 5 respectively (legend only in Figure 5). The PF and MT schedulers have higher average throughput and lower FTP response time compared to BQA. However, the VoIP

end-to-end delay results in Figure 6 show that BQA out-performs PF and MT. Similarly, the video end-to-end delay results (Figure 7) also show that BQA performs better than MT and PF (MT out of range in Figure 5 and 6 due to huge packet delays). TABLE II: MAIN SIMULATION PARAMETERS Parameter

Setting

Cell Layout

3 Cells, 1 eNodeB

System Bandwidth

5 MHz (~25 PRBs)

Frequency reuse factor

1

Cell radius

375m

UE velocity

120kmph

Max UE power

23dBm

Path loss

128.1+37.6log10(R), R in km

Slow fading

Log-normal shadowing, 8dB standard deviation, correlation 1

Fast fading

Jakes-like method [13]

Mobility Model

Random Way Point (RWP)

Power Control

FPC, α = 0.6, P0 = -58dBm

Traffic environment

Loaded

Max FDPS UEs

5

RC size

5

VoIP traffic model Silence/ talk spurt length

Exponential(3) sec

Encoder scheme

GSM EFR

Video traffic model Frame size

1200 bytes

Frame inter-arrival time

75ms

HTTP traffic model Page size

100Kbytes

Page inter-arrival time

12 sec

FTP traffic model File size

20Mbytes

File inter-request time

Uniform distribution, min 80s, max 100s

VoIP, FTP and HTTP Multi-Bearer UEs Scenario In this scenario, multi-bearer UEs with VoIP, FTP and HTTP bearers are simulated. The performance of schedulers is compared in terms of average cell throughput, FTP average upload response time, HTTP page response time and VoIP packet average end-to-end delay. The average cell throughput and FTP graphs are similar to the previous scenario. However, BQA turns out to be the best scheduler for providing VoIP service. It has the least average end-to-end delay for VoIP packets in all the simulations under this scenario. This is illustrated in Figure 20. The HTTP average page response time graphs are depicted in Figure 22 and show acceptable results for BQA, considering the fact that high priority VoIP traffic is present.

Figure 4: Average cell throughput

Figure 5: FTP average upload response time

Figure 6: VoIP average end-to-end delay

Figure 7: Video average end-to-end delay

Figure 8: Average cell throughput

Figure 9: FTP upload response time

Figure 10: VoIP average end-to-end delay

Figure 11: HTTP average page response time

4

Conclusion and Outlook

This paper proposes the BQA scheduler, designed to guarantee QoS provision to the UEs. It maximizes the cell throughput by giving priority to UEs with better channel conditions. Multi-bearer UEs are supported by the scheduler. The scheduler decisions are in accordance with FPC. The scheduler is time and frequency domain decoupled. The resource allocation is performed with bandwidth flexibility, contiguity constraint of subcarriers and UE buffer size consideration. Simulation results confirm QoS provision of the scheduler to UEs. In future, reducing the tree algorithm complexity and implementing Admission Control (AC) functionality would be of interest.

5

Acknowledgment

This is only a version for self-achieving, the final publication is available at link.springer.com under: http://link.springer.com/chapter/10.1007/978-3-642-30630-3_26

6

References

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