We consider scheduling and resource allocation in long-term evolution (LTE) networks across voice over LTE (VoLTE) and best-effort data users. The difference between these two is that VoLTE users get scheduling priority to receive their required quality of service. As we show, strict priority causes data services to suffer. We propose new scheduling and resource allocation algorithms to maximize the sum- or proportional fair (PF) throughout amongst data users while meeting VoLTE demands. Essentially, we use VoLTE as an example application with both a guaranteed bit-rate and strict application-specific requirements. We first formulate and solve the frame-level optimization problem for throughput maximization; however, this leads to an integer problem coupled across the LTE transmission time intervals (TTIs). We then propose a TTI-level problem to decouple scheduling across TTIs. Finally, we propose a heuristic, with extremely low complexity. The formulations illustrate the detail required to realize resource allocation in an implemented standard. Numerical results show that the performance of the TTI-level scheme is very close to that of the frame-level upper bound. Similarly, the heuristic scheme works well compared to TTI-level optimization and a baseline scheduling algorithm. Finally, we show that our PF optimization retains the high fairness index characterizing PF-scheduling.
These three basic scheduling algorithms are modelled and compared in @cite_21 and @cite_1 in terms of both throughput and fairness index. @cite_26 , the authors compare six scheduling schemes including round robin, max rate, Kwan max throughput, MaxMin, PF, and resource fair (RF) via simulations. @cite_18 a new scheduling mechanism is proposed to increase the throughput compared to PF and round robin schedulers, while losing only 20 For multi-tier networks a scheduling algorithm based on PF scheduling and frequency reuse is developed in @cite_37 . The work in @cite_29 develops resource allocation for Coordinated Multi-Point transmission in LTE-Advanced to ensure a good tradeoff between cell-average and cell-edge spectral efficiency. Most of these works consider non-GBR users only (while we propose novel scheduling algorithms which consider two different services non-GBR and GBR services).
@cite_18 @cite_37 @cite_26 @cite_29 @cite_21 @cite_1
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The envisaged high data rates of Long Term Evolution- Advanced (LTE-Advanced) systems necessitate the requirement of high spectral efficiency. To meet the spectral efficiency requirements of LTE-Advanced systems, a novel resource scheduling algorithm is proposed in this paper. Since LTE-Advanced systems are expected to be deployed in a two-tier cell architecture, where femtocells will be deployed as the second tier, the proposed scheduling algorithm employs a resource reuse strategy that reuses resources among femtocells. In addition, the proposed scheduling algorithm uses the Proportional Fair (PF) scheduling principle as its baseline scheduling strategy. An explicit interference coordination strategy as well as a new mechanism to improve the system fairness performance is explored. A system level simulation is carried out to evaluate the performance of the proposed scheduling algorithm in meeting the spectral efficiency requirements of LTE-Advanced systems. Proportional Fair (PF) scheduling algorithms are the de facto standard in cellular networks. They exploit the users' channel state diversity (induced by fast-fading) and are optimal for stationary channel state distributions and an infinite time-horizon. However, mobile users experience a nonstationary channel, due to slow-fading (on the order of seconds), and are associated with base stations for short periods. Hence, we develop the Predictive Finite-horizon PF Scheduling ((PF)2S) Framework that exploits mobility. We present extensive channel measurement results from a 3G network and characterize mobility-induced channel state trends. We show that a user's channel state is highly reproducible and leverage that to develop a data rate prediction mechanism. We then present a few channel allocation estimation algorithms that exploit the prediction mechanism. Our trace-based simulations consider instances of the ((PF)2S) Framework composed of combinations of prediction and channel allocation estimation algorithms. They indicate that the framework can increase the throughput by 15 -55 compared to traditional PF schedulers, while improving fairness. The LTE specification provides QoS of multimedia services with fast connectivity, high mobility and security. However, 3GPP specifications have not defined scheduling algorithms to support real time and non-real time application services. In this paper we propose a two level scheduling scheme composed by cooperative game concept and EXP-RULE scheduling algorithm. By using cooperative game theory such as bankruptcy game and Shapley value, the proposed mechanism works by forming coalition between flow classes to distribute the bandwidth fairly. To make a performance judgment, the proposed downlink scheduling scheme has been compared to other well known schedulers such as M-LWDF and PF. Simulation results show that the proposed scheme can improve the performance on the used metrics among services. The performance evaluation is conducted in terms of system throughput, packet loss ratio (PLR), cell spectral efficiency and fairness Index. Packet scheduler at the medium access control (MAC) layer is essential to improve radio resource utilization in the Long Term Evolution (LTE) network. The MAC scheduler allocates resource blocks to user terminals (UEs) according to the priority metric, which varies in different scheduling algorithms. Although there have been many studies on the performance of LTE schedulers at the MAC layer, it is interesting to evaluate the impact of different LTE MAC schedulers on the transport layer, particularly on the transmission control protocol (TCP). In this study, we implement three mainstream LTE MAC schedulers in Network Simulator-3 (NS-3), namely, maximum throughput (MT), blind equal throughput (BET) and proportional fair (PF). Extensive simulations are conducted to examine the different TCP throughput achieved with the frequency domain version and the time domain version of these schedulers in a vehicular environment. The performance difference is attributed to important factors such as the resource allocation granularity, channel-awareness in scheduling, and the number of UEs.