Buffer-aware resource scheduling scheme for LTE-A uplink relay-assisted network

The Journal of China Universities of Posts and Telecommunications December 2013, 20(6): 30–35 www.sciencedirect.com/science/journal/10058885

http://jcupt.xsw.bupt.cn

Buffer-aware resource scheduling scheme for LTE-A uplink relay-assisted network TANG Yi-wen (), LI Xi, JI Hong, LIU Jian School of Telecommunication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China

Abstract Due to the constraint of single carrier frequency division multiple access (SC-FDMA) adopted in long term evolution (LTE) uplink, subcarriers allocated to single user equipment (UE) must be contiguous. This contiguous allocation constraint limits resource allocation flexibility and makes the resource scheduling problem more complex. Most of the existing work cannot well meet UE’s quality of service (QoS) requirement, because they just try to improve system performance mainly based on channel condition or buffer size. This paper proposes a novel resource scheduling scheme considering channel condition, buffer size and packet delay when allocating frequency resource. Firstly, optimization function is formulated, which aims to minimize sum of weight for bits still left in UE buffer after each scheduling slot. QoS is the main concern factor here. Then, to get packet delay information, this paper proposes a delay estimation algorithm. Relay node (RN) is introduced to improve overall channel condition. Specific RN selection strategy is also depicted in the scheme. Most important of all, a creative negotiation mechanism is included in the subcarrier allocation process. It can improve the overall system throughput performance in guarantee of user’s QoS requirement. Simulation results demonstrate that the scheme can greatly enhance system performance like delay, throughput and jitter. Keywords

SC-FDMA, relay, scheduling, LTE-A, MBDF, BDF-PF

1 Introduction Orthogonal frequency division multiple access (OFDMA) as a key technology introduced by LTE and LTEadvanced (LTE-A) can greatly increase system throughput and spectrum efficiency. However, OFDMA also makes instantaneous transmit power vary dramatically within a single OFDM symbol. Such an undesirable high peak-to-average power ratio (PAPR) is a serious concern for the uplink (UL). As an alternative to OFDMA, single carrier frequency division multiple access (SC-FDMA) has been applied in LTE UL transmission. SC-FDMA has significantly lower PAPR and keeps most advantages of OFDMA. Compare with OFDMA, SC-FDMA brings more constraints because of single-carrier characteristic.

Received date: 19-06-2013 Corresponding author: TANG Yi-wen, E-mail: [email protected] DOI: 10.1016/S1005-8885(13)60105-3

Resource block (RB) allocated to the same UE must be contiguous, which is RB contiguous constraint. Besides, RBs of same UE must use the same modulation and coding scheme (MCS) [1]. This constraint is robust MCS mode constraint. In addition, resource scheduler cannot obtain delay information in UL. All of the constraints above bring great challenges for UL resource scheduling research. Recently, UL resource scheduling algorithms can be divided into two categories: channel-based and bufferbased [2–3]. In those literatures of channel-based, different allocation strategies are put forward in consideration of RB contiguous constraint and robust MCS mode constraint [4–5]. In Ref. [6], the riding peaks algorithm is proposed, which tries to use each user’s highest valued RBs as much as possible. This algorithm assigns a RB to a user that already has allocated RBs if they are neighbors. In Ref. [7], authors propose a complex algorithm with many RBs’ swap to find a better allocation solution. Those channel-based scheduling algorithms

Issue 6

TANG Yi-wen, et al. / Buffer-aware resource scheduling scheme for LTE-A uplink relay-assisted network

cannot well meet UE’s QoS requirement as a result of neglecting the UE’ buffer status. As for small number of buffer-based UL scheduling algorithms, buffer status and channel condition are main concern elements to achieve better system performance. In Ref. [8], a buffer-based scheduling algorithm is introduced to minimize packet loss and increase resource utilization efficiency while ensuring fairness. However, rarely do authors apply the packet delay information because of imperfect buffer status report (BSR). The overall system delay performance cannot be guaranteed. In this paper, a novel resource scheduling scheme for LTE-A UL transmission was proposed. Firstly, an optimization equation with channel condition, buffer size and packet delay is constructed. Optimization object is to improve whole system’s QoS performance by minimizing sum of weight for each bit after every scheduling slot. Then, a delay estimation approach is included to provide delay information. Packet delay can be estimated by recording arrival time of BSR. In addition, relay node (RN) is introduced to enhance general channel condition of UEs near cell edge. Most important of all, this paper uses a creative negotiation mechanism when allocating RBs to UEs. Sum of allocation metric can be maximized through negotiation between UEs and RBs. The overall delay and throughput performance can be enhanced obviously. The rest of this paper is organized as follows. Sect. 2 describes the UL transmission system model. Sect. 3 analyzes resource allocation problem and formulate optimization function. Then, delay estimation scheme and RN selection algorithm are introduced in Sect. 4. Specific resource allocation algorithm is also depicted in detail here. Simulation results and related analysis are shown in Sect. 5. Finally, this paper is concluded in Sect. 6.

2 System model

31

while UEs associated with RNs are indirect UEs.

Fig. 1

System model

Each UE must report buffer status to their serving eNB via BSR periodically or event-triggered [10]. Buffer size of each UE is included in BSR. UL channel condition is measured by eNB. All the buffer size and channel condition information are passed to the scheduler of eNB. Scheduler makes resource scheduling decision in interval of scheduling slot T and resources are allocated to UEs in granularity of RB.

3 Problem formulation To improve overall throughput and delay performance of system, channel condition, buffer size and packet delay are considered as the main factors in problem formulation. Regard delay as the weight of each bit in UE buffer and utility function can be seen as: Lk

S = ∑∑ Dk,i k

(1)

i=1

where Dk,i is delay of bit i in buffer of UE k, Lk is buffer size, S is sum of utility. It is obvious to see that S can reveal the overall buffer size and delay information. The object can be converted to minimize S after each scheduling slot. Assume that all packets arrive at the beginning of each slot and bit rate of the UE k can obtain after scheduling is: (2) rk = ∑ rk,m m∈M k

where rk,m denotes maximum rate that UE can achieve on This paper mainly focuses on a two-hop relay-assisted LTE-A cellular network. The link between evolved node B (eNB) and RN use the same carrier frequency as the link between RN and UE. RN can operate in full-duplex mode [9]. As shown in Fig. 1, consider N RNs are placed near the cell edge. UL system bandwidth is divided into a set number of RBs and active UEs are randomly positioned in the cell with uniform distribution. Each UE is connected to eNB or RN based on experienced signal-tonoise ratio (SNR). UEs associated with eNB are direct UEs,

RB m. M k defines the contiguous RBs’ set owned by UE. When a scheduling slot is over, buffer size of UE k is: Lk′ = max ( 0, Lk − rk T ) (3) where T is the duration of a scheduling slot. If buffer is not empty, bits remain in buffer can be derived as min ( rk T , Lk ) + 1 , min ( rk T , Lk ) + 2,..., Lk . Based on above information, optimization problem can be treated as minimization of S after each scheduling slot. Optimization equation can be given by:

32

The Journal of China Universities of Posts and Telecommunications

Lk ⎛ ⎛ ⎞⎞ arg min ⎜ ∑ ⎜ (Dk,i +T ) ⎟ ⎟ (4) ∑ ⎜ ⎟⎟ ⎜ k i= min ( rk T,Lk )+1 ⎠⎠ ⎝ ⎝ The optimization equation can be deduced as follows, it describes system’s actual throughput and delay condition. ⎛ min( Lk , rk T ) ⎞ arg max ⎜ ∑ ∑ ( Dk ,i + T ) ⎟ (5) i =1 ⎝ k ⎠

4 Resource scheduling scheme Three parts are included in whole scheme: delay estimator, RN selector and resource allocator. Delay estimator estimates delay of packets according to BSRs arrival information. RN selector decides whether UE should send message through RN and choose the RN with best channel condition for UEs. Resource allocator uses both channel condition and buffer status information to make allocation decision. Contiguous RBs are selected to fulfill the QoS requirement of different UEs. 4.1

Delay estimation algorithm

Assume that buffer size reported by BSR is Lk and BSR arrives at time Tk , j , packet size Lk , j is:

Lk , j = Lk − Lk′

(6)

where j denotes new packet’s index in buffer and Lk′ denotes old UE buffer size recorded by scheduler. Lk′ is updated and used to decide the maximum rate witch UE can achieve every scheduling slot. Tk , j can be regarded as the arrival time of new packet. Therefore, let T0 be present time, scheduler can obtain each packet’s duration Dk , j in buffer from eNB side.

Dk , j = T0 − Tk , j 4.2

(7)

RN selection algorithm

Let γ k be the average SNR of UE k to eNB directly,

γ n , k be the condition of UE k to RN n and γ n be the condition of RN n to eNB. As the channel condition of indirect UE to eNB via determined RN is decided by the worst channel condition of those direct-associated links (UE-RN or eNB-RN), consider the general channel condition of UE k to eNB via RN n as: (8) γ kn = min ( γ n , k , γ n ) Choose the best indirect RN n′ as follows:

γ kn ' = min ( γ kn ) If γ

n n' k

2013

(9)

> (1 + α ) γ k , UE k can be added into the indirect

UE group and RN n′ is selected as the associated RN. α is the RN selection factor determined by channel condition stability and specific RN type. γ kn′ can be seen as the general channel condition of UE k to eNB. After the related RN is determined, SNR on RB m for each indirect UE to eNB should also be calculated: γ n′, k , m = min(γ n , k , m , γ n , m ) (10) where γ n , k , m denotes the channel condition on RB m for RN n to UE k and γ n, m denotes the channel condition on RB m for RN n to eNB. 4.3

Resource allocation algorithm

Optimization equation in Eq. (5) can be simplified as follows: ⎛ ⎞ arg max ⎜ ∑ min ( rk T , Lk ) Dk ( rk ) ⎟ (11) ⎝ k ⎠

Dk ( rk )

is average delay after a slot for those

transmitted bits. It is a decreasing function with rk . The object can be maximized if more system resources are allocated to transmit the bits with higher delay. It’s reasonable to give higher priority to those users with higher delay and better channel condition. To solve the problem efficiently, this paper introduces an approximate equation: ⎛ ⎛ ⎛ ⎞ ⎞⎞ (12) arg max ⎜⎜ ∑ ⎜ min ⎜ ∑ ak , m rk , mT , Lk ⎟ Dk ⎟ ⎟⎟ ⎝ m ⎠ ⎠⎠ ⎝ k ⎝ where ak , m denotes the RB allocation indicator. ak , m = 1 if RB m is allocated to UE k, else ak , m = 0 . According to the Eq. (12), allocation metric U k , m of UE k on RB m is: U k , m = rk , m Dk

(13)

Regard the algorithm using this metric as minimum bit delay first (MBDF) algorithm. Meanwhile, another metric which improves fairness between UEs is also introduced here. r D U k , m = k,m k (14) Rk

Rk denotes average transmitted rate in a time window. This algorithm is bit delay first-proportional fair (BDF-PF) algorithm.

Issue 6

TANG Yi-wen, et al. / Buffer-aware resource scheduling scheme for LTE-A uplink relay-assisted network

After selecting maximum U k , m for RB m, scheduler should decide whether allocate it to UE k in accordance with contiguous RB allocation constraint. It is important that RB m allocated to UE k should increase the actual throughput of UE k. When UE can transmit all data with the pre-allocated RBs, no more RBs should be allocated to this UE. Poor condition RB should not be allocated to UE if the RB decreases the actual throughput because of worse SNR. The contiguous RB allocation constraint of SC-FDMA is sufficient to make RB allocation problem harder. It is proved to be a NP-hard problem [6], This paper proposes a sub-optimal solution here. K denotes the set of UEs that needs RBs (RB set is M). Since number of MCS is limited, different RBs could use the same MCS. Moreover, MCS of UE is decided by RB with poorest condition. That means requirement of single UE can be fulfilled by many kinds of RB sets. Considering allocation of RBs as a game with many constraints among different UEs, a negotiation mechanism between UEs can be introduced because requirement of each UE can be fulfilled by multiple RB sets. As shown in Fig. 2, RB set {2, 3} has been allocated to UE1 and RB set {4,5} has been allocated to UE2. UE1’s rate requirement can be met while UE2’s cannot, meanwhile, UE1’s rate requirement can also be met by RB set {1, 2}. It is reasonable to seize RB3 from UE1 for UE2 and UE1 can shift its RB set left to use RB1. In addition, there may be more than one RB candidate sets selected by scheduler successively. This can be seen as a game which also needs negotiation between RB sets. In Fig. 3, RB set {5} has been allocated to UE1, but its requirement cannot be fulfilled. It is better to re-allocate the RB set {1, 2, 3} to the hungry UE1.

33

Based on the above analysis, this paper introduces two concepts called main set Fk and alternative set Gk . RBs in Fk

could be used to transmit packets after RB

allocation process. Those RBs can be replaced by others belong to Gk during allocation process. Fk ⊂ Gk . RBs in each set are contiguous and worst MCS of RBs in Fk is equal to RBs in Gk . If Fk cannot meet UE’s requirement, UE will try to seize neighbour RBs next to Fk by negotiation. The adjacent RB can be re-allocated to this UE if satisfies following conditions: the re-allocated RB can achieve higher metric for this UE than others (those UEs whose requirements have not been met yet); Pre-owner of re-allocated RB can get the alternative RB to meet rate requirement directly or through another negotiation. Update of Fk should not decrease sum of pre-allocated RBs’ metric. Every time, find maximum U k , m whose allocation indicator δ k , m (which prevents closed loop) is equal to 1 for UE in K. Add the selected RB into two temporary candidate sets Fk′ and Gk′ , let Qk , m denote MCS index for UE on different RB, Qk ,worst = Qk , m , expand along Fk′ until adjacent RBs cannot be added into any sets. RB m′ can be added into Fk′ or Gk′ if one of following conditions is met: 1) m′ ∈ M , U k , m′ is the largest among metrics of UEs belong to K on the same RB m′ , m′ will not decrease the achievable rate of Gk′ . If requirement of UE k cannot be met through Fk′ , let Gk′ = Gk′ + {m′} , Fk′ = Fk′ + {m′} and Qk ,worst = min ( Qk , m , Qk ,worst ) . Else if requirement of

UE can be met and

Qk ,worst

is equal to

Qk , m′ ,

Gk′ = Gk′ + {m′} . Else RB cannot be added into any sets. 2) If m′ ∉ M and m′ ∉ Fk , requirement of UE k cannot be met either, check whether m′ can be seized by k through negotiation. If so, Gk′ = Gk′ + {m′} and Fk′ = Fk′ + {m′} . Else RB m′ cannot be added into neither Fk′ nor Gk′ .

Fig. 2

UE negotiation example

and m ' ∈ Fk ˈ which means Fk′ and Fk are adjacent. Refresh Fk′ and Gk′ according to Fk 3) If m ' ∉ M

and rate requirement of UE. If there is one RB which cannot be added to Gk′ from previous Fk′ , stop RB expansion above. Compare Fk′ and Fk at each end of RB expansion Fig. 3

Re-allocation example

process until finding the optimal Fk for UE. Allocation

34

The Journal of China Universities of Posts and Telecommunications

algorithm is depicted in detail as follows: Step 1 Find those UEs with non-empty buffer, initialize the UE set K and RB set M, let Fk = Gk = ∅ . Construct the UE-RB metric matrix U and MCS matrix Q. Step 2 If K or M is empty, go to Step 6. Else, find the highest U k , m in U for UE in K and RB in M. Let

2013

excellent delay performance. Moreover, MBDF is more excellent to the UEs with better channel condition, while BDF-PF can provide better latency to the UEs with poor channel condition.

Fk′ = Gk′ = {m} , then go to Step 3. Step 3 Expand along Fk′ until adjacent RB cannot be added into neither Fk′ nor Gk′ in both directions. Go to Step 4. Step 4 Compare metric sum on Fk and Fk′ , if that of Fk′ is larger, let δ k , m = 0 to m ∈ Fk , M = M + Fk − Fk′ ,

Fk = Fk′ and Gk = Gk′ . Go to Step 5. Step 5 If requirement is met, K = K − {k} . Go to Step 2. Step 6 Update the overall bit rate information for each UE and send indicator message through the wireless channel.

5 Simulation results To evaluate the performance of scheme, uplink system level simulations have been conducted on 3GPP LTE system model of NS-3 simulator. The simulation scenario considers a single cell of radius 1.5 km. 3 RNs are positioned in the cell edge uniformly. Each RN is 1.0 km far from eNB. Let total number of active UEs be 25 corresponding to the number of RB, UEs’ positions also obey uniform distribution. Each UE will transmit a 1 024 B packet in 10 ms interval. This paper performs simulation to compare performance of MBDF, BDF-PF, maximum throughput (MT) and proportional fair (PF) algorithm based on buffer size. RN selection strategy is the same to make sure the impact of different resource allocation algorithms. The simulation investigates packet delay as well as average UE throughput. Results will be shown in form of cumulative distribution function (CDF) curve. Fig. 4 compares the average delay performance among different scheduling algorithms. Most UE’s average packet delay can be lower than 160 ms except MT. It can be regarded as the result of neglecting buffer status, while other three take the buffer status into consideration. Compared with PF, MBDF and BDF-PF which take the average delay as an optimal factor can achieve more

Fig. 4

Average delay performance

In Fig. 5, average UE throughput performance is shown. It is obvious that throughput performances of MBDF and BDF-PF are more excellent than PF which owe to the creative introduction of negotiation mechanism. When it comes to MT, some UEs’ average throughput can reach to 800 kbit/s, but more UEs’ are lower than 200 kbit/s, the overall performance is worse than MBDF and BDF-PF. It is also obvious that MBDF provides higher overall throughput performance, hower, BDF-PF provides more fairness.

Fig. 5

Average UE throughput performance

The comparison of delay jitter is also included in simulation results. Jitter can reveal the stability of delay varying to single UE. As depicted in Fig. 6, Jitter performance of MT is the worst because of reliance on channel condition. Most UEs’ jitter can be lower than 40 ms for MBDF, BDF-PF and PF. CDF curve of PF is smooth and cliffy because of only consideration in fairness, every UE experiences similar packet variation condition. In MBDF and BDF-PF, lots of UEs’ jitter performance enhances greatly by sacrificing the rest small part of UEs’ jitter performance. The tradeoff is worthwhile considering

Issue 6

TANG Yi-wen, et al. / Buffer-aware resource scheduling scheme for LTE-A uplink relay-assisted network

delay performance improvement.

35

References 1. 3GPP TS36.213 v9.2.0. Evolved Universal Terrestrial Radio Access (E-UTRA); Physical layer procedures. 2010 2. Ren F, Xu Y, Yang H, et al. Frequency-domain packet scheduling with stability analysis for 3GPP LTE uplink. IEEE Transactions on Mobile Computing, 2013, 12(12): 2412−2426 3. Yang H K, Ren F Y, Lin C, et al. Frequency-domain packet scheduling for 3GPP LTE uplink. Proceedings of the 29th Annual Joint Conference of the IEEE Computer and Communications (INFOCOM’10), Mar 14−19, 2010, San Diego, CA, USA. Piscataway, NJ, USA: IEEE, 2010: 9p 4. Wei Y J. PF scheduling algorithm research based on user grouping for

Fig. 6

Jitter performance

6 Conclusions This paper has considered the UL scheduling problem in relay-assisted LTE-A networks. Through the analysis of system characteristics, a delay estimation and relay selection strategy is suggested. Most important, a novel approach of implementing scheduler is also included here, which make full use of channel condition and buffer status information. Negotiation aiming at maximizing the total metric of all UEs is applied in the resource allocation process. Simulation results indicate that proposed scheme provides great enhancement in UE throughput and delay performance while guaranteeing stable jitter. Acknowledgements This work was supported by the National Science and the Technology Major Project (2011ZX03001-007-03), the National Natural Science Foundation of China (61302080, 61271182).

LTE-advanced system with carrier aggregation. The Journal of Chongqing University of Posts and Telecommunications: Natural Science, 2013, 25(3): 310−313 (in Chinese) 5. Yaacoub E, Dawy Z. A game theoretical formulation for proportional fairness in LTE uplink scheduling. Proceedings of the Wireless Communications and Networking Conference (WCN’09), Apr 5−8, 2009, Budapest, Hungary. Piscataway, NJ, USA: IEEE, 2009: 5p 6. Suk-Bok L, Pefkianakis I, Meyerson A, et al. Proportional fair frequency-domain packet scheduling for 3GPP LTE uplink. Proceedings of the 28th Annual Joint Conference of the IEEE Computer and Communications (INFOCOM’09), Apr 19−25, 2009, Rio de Janeiro, Brazil. Piscataway, NJ, USA: IEEE, 2009: 2611−2616 7. Chang C H, Chao H L, Liu C L. Sum throughput-improved resource allocation for LTE uplink transmission. Proceedings of the 74th Vehicular Technology Conference (VTC-Fall’11), Sep 5−8, 2011, San Francisco, CA, USA. Piscataway, NJ, USA: IEEE, 5p 8. Mehta M, Khakurel S, Karandikar A. Buffer-based channel dependent Uplink scheduling in relay-assisted LTE networks. Proceedings of the Wireless Communications and Networking Conference (WCNC’12), Apr 1−4, 2012, Paris, France. Piscataway, NJ, USA: IEEE, 2012: 1777−1781 9. 3GPP TR36.806 v9.0.0. Evolved Universal Terrestrial Radio Access (E-UTRA); Relay architectures for E-UTRA (LTE-advanced). 2010 10. 3GPP TS36.321 v9.2.0. Evolved Universal Terrestrial Radio Access (E-UTRA); Medium Access Control (MAC) protocol specification. 2010

(Editor: WANG Xu-ying)