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.
Scheduling is one of the most important components in LTE systems: the scheduler, implemented at the eNodeB (eNB), distributes the limited available time frequency resources among the active users in order to satisfy their QoS needs @cite_16 @cite_11 . The 3GPP specifications do not specify scheduling policies, making the scheduling algorithm vendor-specific @cite_12 . There are several works that have proposed and compared various scheduling algorithms; however, in general, these do not use an optimization framework to maximize a chosen metric (such as our choice of sum rate or PF rate) while meeting constraints set by GBR users. In this paper we focus on VoLTE users; the principles developed here could be extended to other GBR flows.
@cite_16 @cite_12 @cite_11
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In this paper, we introduce an approach for application-aware resource block scheduling of elastic and inelastic adaptive real-time traffic in fourth generation Long Term Evolution (LTE) systems. The users are assigned to resource blocks. A transmission may use multiple resource blocks scheduled over frequency and time. In our model, we use logarithmic and sigmoidal-like utility functions to represent the users applications running on different user equipments (UE)s. We present an optimal problem with utility proportional fairness policy, where the fairness among users is in utility percentage (i.e user satisfaction with the service) of the corresponding applications. Our objective is to allocate the resources to the users with priority given to the adaptive real-time application users. In addition, a minimum resource allocation for users with elastic and inelastic traffic should be guaranteed. Every user subscribing for the mobile service should have a minimum quality-of-service (QoS) with a priority criterion. We prove that our scheduling policy exists and achieves the maximum. Therefore the optimal solution is tractable. We present a centralized scheduling algorithm to allocate evolved NodeB (eNodeB) resources optimally with a priority criterion. Finally, we present simulation results for the performance of our scheduling algorithm and compare our results with conventional proportional fairness approaches. The results show that the user satisfaction is higher with our proposed method. Designing scheduling algorithms that work in synergy with TCP is a challenging problem in wireless networks. Extensive research on scheduling algorithms has focused on inelastic traffic, where there is no correlation between traffic dynamics and scheduling decisions. In this work, we study the performance of several scheduling algorithms in LTE networks, where the scheduling decisions are intertwined with wireless channel fluctuations to improve the system throughput. We use ns-3 simulations to study the performance of several scheduling algorithms with a specific focus on Max Weight (MW) schedulers with both UDP and TCP traffic, while considering the detailed behavior of OFDMA-based resource allocation in LTE networks. We show that, contrary to its performance with inelastic traffic, MW schedulers may not perform well in LTE networks in the presence of TCP traffic, as they are agnostic to the TCP congestion control mechanism. We then design a new scheduler called “Queue MW” (Q-MW) which is tailored specifically to TCP dynamics by giving higher priority to TCP flows whose queue at the base station is very small in order to encourage them to send more data at a faster rate. We have implemented Q-MW in ns-3 and studied its performance in a wide range of network scenarios in terms of queue size at the base station and round-trip delay. Our simulation results show that Q-MW achieves peak and average throughput gains of 37 and 10 compared to MW schedulers if tuned properly. 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. 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.