A Cross-Layer Proportional Fair Scheduling Algorithm with Packet Length Constraint in Multiuser OFDM Networks

The Proportional Fair (PF) scheduler has been extensively studied in wireless communications research. Most of the research done, however, focuses on theoretical or simplistic simulations. In this paper, both theory and practical measurements for a PF scheduler are studied. Two data collections are conducted to verify the performance of the scheduler in an actual LTE-A network (small cells) environment. Allocated Physical Resource Blocks (PRBs) and throughput of each phone used in the data collection are estimated. Three different types of PF schedulers are implemented to predict user throughput. The results show that the scheduler maintains good fairness for both user throughputs and PRB allocation. Further it is shown that our results, derived from actual recorded data are different from those derived from simulation models presented in the literature [1] [2]. Similarly, the cell throughput and fairness values are dynamic and randomly distributed with the time in an actual LTE-A network in contrast to simulation models. From our study, we show that the generalize PF Scheduler performs more accurately to predict the user throughput values. It is concluded that this real-world LTE-A network study is more meaningful and valuable in enhancing the understanding of actual 4G and future 5G networks.

Resource allocation (RA) for OFDMA has been extensively researched with the objective of maximizing capacity while serving users in a fair manner. However, most of the previous works have focused on achieving these requirements per symbol (instantaneously). On the other hand proportional fair (PF) scheduling which is widely deployed in 3G data networks achieves the system objectives over a certain time, thus adding flexibility and increasing the system throughput. PF scheduling has been modified to work in OFDMA in a few studies, but they have extended the scheme without making use of the additional capacity increase that can be achieved by considering individual relative subcarrier responses. In this paper we propose a simple subcarrier opportunistic proportional fair (SOPF) scheduling scheme specifically suited to OFDMA. It includes a measure that makes the allocation assign the subcarrier to the user who has the best response relative to the average response of that subcarrier with the rest of the users. The result is that our SOPF scheme achieves a capacity-fairness measure above the traditional PF scheme.

Long Term Evolution(LTE) 시스템은 멀티미디어 서비스와 같은 다양한 서비스를 이동 사용자에게 제공할 수 있다. 실제로 HSPA+(High Speed Packet Access plus)는 다운링크의 비트 율(bit rate)을 크게 향상 시켰으나, 다양한 멀티미디어 서비스에서 요구하는 서비스 품질을 어떻게 만족시킬 것인가에 대한 연구는 매우 미비한 상태이다. 본 논문에서는 proportional fair(PF) 알고리즘을 기반으로 하여 LTE를 위한 효율적인 패킷 스케쥴링 알고리즘을 제안하였다. 제안된 알고리즘에서는 패킷 스케쥴링을 할 때 패킷의 우선순위를 결정하는 가장 중요한 요소인 트래픽 클래스의 가중치와 순간 사용자 데이터 전송율을 최적화 하였다. 또한 다중 셀(multi-cell) 환경에서 LTE를 통해서 사용자에게 전송되는 멀티미디어 트래픽을 시뮬레이션 함으로써 제안된 알고리즘의 성능이 향상되었음을 보였다. The Long Term Evolution (LTE) system is already able to provide a background of variety services for mobile users with multimedia services such as audio, video, and data. In fact, the High Speed Packet Access plus (HSPA+) solution can greatly enhance bit rates on down-link. However, the supporting for multimedia applications with different QoS (Quality of Service) requirements is not devised yet. Hence, in this paper we propose an effective packet scheduling algorithm based on Proportional Fairness (PF) scheduling algorithms for the LTE. In this proposed packet scheduling scheme, we optimized instantaneous user data rates and the traffic class weight which prioritize user's packets. Finally, we evaluated and showed the performance of the proposed scheduling algorithm through simulations of multimedia traffics being transmitted to users over LTE links in a multi-cell environment.

An opportunistic feedback technique is proposed for proportional fair (PF) scheduling in a downlink multi-user system. This technique requires each mobile station, the scheduling metric of which is higher than a threshold, to send one-bit feedback for PF scheduling. The scheduler determines the optimal modulation and coding scheme for a scheduled user based on channel quality indicator (CQI) update, which is sent on a longer period than the scheduling period. The simulation results indicate that PF scheduling with the proposed update scheme can achieve similar performance as PF scheduling with full CQI feedback. The feedback overhead can be reduced in comparison with typical PF scheduling provided that an optimal CQI update period is chosen.

In this paper, we study resource management models and algorithms that satisfy multiple performance objects simultaneously. We realize the proportional fairness principle based QoS model, which defines both delay and loss rate requirements of a class, to include fairness, which is important for the integration of multiple service classes. The resulting Proportional Fairness Scheduling model formalizes the goals of the network performance, user’s QoS requirement and system fairness and exposes the fundamental tradeoffs between these goals. In particular, it is difficult to simultaneously provide these objects. We propose a novel scheduling algorithm called Proportional Fairness Scheduling (PFS) that approximates the model closely and efficiently. We have implemented the PFS scheduling in Linux. By performing simulation and measurement experiments, we evaluate the delay and loss rate proportional fairness of PFS, and determine the computation overhead.

Multiple-input multiple-output (MIMO) wireless communications systems have attracted a lot of attentions, because of their potential for high gain in channel capacity. Recently, attention has shifted to multiuser MIMO (MU-MIMO) systems. In the schemes for downlink MU-MIMO system, dirty paper coding (DPC) and block diagonalization (BD) algorithms can provide higher sum rate capacity of MU-MIMO systems; however, exhaustive user scheduling for them may cause prohibitive computation complexity. The greedy scheduling algorithms were proposed for DPC and for BD; and proportionally fair (PF) scheduling for MU-MIMO was also discussed in the previous works. However, the discussions in where mainly based on the system model with equal average signal to noise power ratio (SNR) users. In this paper, we focus on the user scheduling for the downlink of MU-MIMO systems with DPC transmission scheme, where each user is assumed to have only one receive antenna, which will simplify the analysis and is expected to give more insight of PF scheduling. We also assume each individual user has different average transmit SNR in the system. We modify the conventional user scheduling algorithm for DPC to modified Gram-Schmidt orthogonalization (M-GSO) based algorithm and extend it into PF scheduling. We also propose a modified PF metric corresponding to the unequal SNR users system model, that increases the sum rate capacity of MU-MIMO system.

We define and evaluate the downlink flow-level capacity of a fractionally loaded OFDMA network utilizing round robin (RR) or proportional fair (PF) scheduling. The flow-level capacity is the maximum traffic intensity that can be supported by a sector while satisfying a minimum flow throughput requirement for bursty, elastic traffic. We obtain a simple, insightful capacity expression for RR scheduling; for PF scheduling, we exploit a fast convergence property of the multi-user diversity gain to implement a computationally efficient, iterative algorithm to solve for the capacity. A hybrid simulation/analysis approach is applied, where a detailed rate distribution obtained via simulation is used as input to a generalized processor sharing queue model. The analytical expressions and numerical results indicate that enhancement of edge throughputs can significantly improve the flow-level capacity.

In this paper, we theoretically study the proportional fair (PF) scheduler in the context of ultra-dense networks (UDNs). Analytical results are obtained for the coverage probability and the area spectral efficiency (ASE) performance of dense small cell networks (SCNs) with the PF scheduler employed at base stations (BSs). The key point of our analysis is that the typical user is no longer a random user as assumed in most studies in the literature. Instead, a user with the maximum PF metric is chosen by its serving BS as the typical user. By comparing the previous results of the round-robin (RR) scheduler with our new results of the PF scheduler, we quantify the loss of the multi-user diversity of the PF scheduler with the network densification, which casts a new look at the role of the PF scheduler in UDNs. Our conclusion is that the RR scheduler should be used in UDNs to simplify the radio resource management (RRM).

SUMMARYIn this paper we study the resource allocation problem for the multiuser orthogonal frequency division multiplexing (OFDM)‐based cognitive radio (CR) systems with proportional rate constraints. The mutual interference introduced by primary user (PU) and cognitive radio user (also referred to secondary user, SU) makes the optimization problem of CR systems more complex. Moreover, the interference introduced to PUs must be kept under a given threshold. In this paper, the highest achievable rate of each OFDM subchannel is calculated by jointly considering the channel gain and interference level. First, a subchannel is assigned to the SU with the highest achievable rate. The remaining subchannels are always allocated to the SU that suffers the severest unjustness. Second, an efficient bit allocation algorithm is developed to maximize the sum capacity, which is again based on the highest achievable rate of each subchannel. Finally, an adjustment procedure is designed to maintain proportional fairness. Simulation results show that the proposed algorithm maximizes the sum capacity while keeping the proportional rate constraints satisfied. The algorithm exhibits a good tradeoff between sum capacity maximization and proportional fairness. Furthermore, the proposed algorithm has lower complexity compared with other algorithms, rendering it promising for practical applications. Copyright © 2011 John Wiley & Sons, Ltd.

We consider the problem of selective relaying in multi-hop networks. At each slot, a relay and a node along the optimal non-cooperative path are opportunistically selected to transmit to the next-hop node in a cooperative manner. Being a promising scheme for fair resource allocation, the proportional fair scheduling (PFS) algorithm provides excellent balance between throughput and fairness via multi-user diversity and game-theoretic equilibrium. To maximize the overall utility along a cooperative multi-hop path, we apply the proportional fair (PF) criterion in selecting nodes and relays for cooperative transmission. Furthermore, we analyze and provide an analytical expression for end-to-end throughput of an opportunistic relaying, cooperative multi-hop path with proportional fairness constraints over a Rayleigh flat-fading channel. To our knowledge, it is the first time that a closed-form expression is obtained for the throughput of a proportional fair relaying, cooperative multi-hop path. This research is an extension of previous theoretical work on PF for cellular networks.

In wireless fading channels, multi-user scheduling has the potential to boost the spectral efficiency by exploiting diversity gains. In this regard, proportional fair (PF) scheduling provides a solution for increasing the users' quality of experience by finding a balance between system throughput maximization and user fairness. For this purpose, precise instantaneous channel state information (CSI) needs to be available at the transmitter side to perform rate adaptation and scheduling. However, in practical setups, CSI is impaired by, e.g., channel estimation errors, quantization and feedback delays. Especially in centralized cloud based communication systems, where main parts of the lower layer processing is shifted to a central entity, high backhaul latency can cause substantial CSI imperfections, resulting in significant performance degradations. In this work robust rate adaptation as well as robust PF scheduling are presented, which account for CSI impairments. The proposed rate adaptation solution guarantees a fixed target outage probability, which is of interest for delay critical and data intensive applications, such as, video conference systems. In addition to CSI imperfections the proposed scheduler is able to account for delayed decoding acknowledgements from the receiver.

A modified proportional fairness (PF) scheduling scheme for OFDMA systems with imperfect channel quality indicator is suggested. It is based on user grouping, and in system level simulations, the proposed scheme improves average user throughput considerably when compared to conventional PF scheduling without grouping.

This paper studies the fairness, power allocation, and channel state information (CSI) quantization in multiuser systems utilizing multiple feedback bits per user. For a given set of schedulers, we obtain the system throughput with different power allocation strategies and any combination of different fading distributions. Moreover, the system performance under user different outage probability constraints is investigated. Assuming homogenous users, as a special case, the throughput is determined for fixed and random request networks. Considering nonidentical fading channels between the transmitter and receivers, the throughput is found under the K-significant average feedback bit allocation technique, and two suboptimal fairness schemes are investigated which satisfy different quality-of-service requirements. The results show that using optimal power allocation, the first quantization region (QR) of each user is the only QR for which no power may be allocated. The system outage probability vanishes as the number of users goes to infinity. Users hard outage probability constraints can be satisfied at the cost of one more QR in the channel quantizer. Finally, the proposed fairness schemes are more flexible than the standard proportional fair (PF) scheduling in dealing with the throughput-fairness tradeoff. However, their superiority over PF scheduling depends on the fairness constraint.

In this work we investigate the influence of smart antenna concepts in the downlink of third generation mobile communication systems (3G) like UMTS (Universal Mobile Telecommunication System) when packet scheduled transmission over downlink shared channels (DSCH) is carried out. We consider hexagonal site structures that are subdivided in three or six subsectors or cells. For the three sector case we investigate smart antenna concepts that use antenna arrays of two and four antenna elements. We illuminate beampointing and fixed beam switching and assume transmission of delay tolerant data such as E-mail or download applications utilising shared channels. Users are scheduled to shared code resources in a time multiplexed manner, where proportional fair and throughput fair scheduling algorithms are investigated. Results are presented in terms of average user throughput figures obtained from system level simulations. A significant increase in system packet data throughput shows when smart antenna concepts with four antenna elements are applied.

LTE-Advanced offers significantly higher data rates than the legacy system. The carrier aggregation (CA) technology allows scalable expansion of effective bandwidth provided to user equipment (UE) through simultaneous utilization of radio resources across multi-component carriers. In this paper we propose a new packet scheduling (PS) criterion algorithm that satisfies the fairness among the different kinds of UEs by designing a weighting factor to proportional fair (PF) packet scheduling (PS) algorithms, while enhancing their throughput performance. The proposed PS algorithm is implemented and validated in a PS module for LTE/LTE-Advanced via system level simulations. Results show that PS-enhanced algorithm achieve higher throughput for both LTE and LTE-Advanced UEs.