Abstract:Abstract-Fourth Generation Networks will almost invariably adopt OFDMA (Orthogonal Frequency Division Multiple Access) and MIMO (Multiple Input-Multiple Output technologies, in order to meet high data rate and Quality of Service (QoS) requirements. The Worldwide Interoperability for Microwave Access (WiMAX) MAC Layer, which is based on the IEEE 802.16 standard, is designed to support a variety of applications, including voice and multimedia services. The problem of providing QoS in broadband wireless systems i… Show more
“…However, for 50 users, it is observed that WFQ and PF, t c = 500, experience longer delay of 2s at the cost of facilitating fairness among users. On the contrary, the PF with t c =50K achieves lower delay of approximately 1s, whilst the Greedy scheduler achieves the lowest delay as agrees in [14] for a greedy type of scheduler serving VOIP. The trade-off of a greedy scheduler is that it sacrifices the fairness among users though it has the lowest delay from all the simulated schedulers in our scenario.…”
Section: B Multiple Sss and Downlink Scheduling Analysismentioning
Abstract-WiMAX performance evaluation considering different scheduling techniques has received considerable attention by WiMAX researchers and also WiMAX operators. The standard does not define MAC scheduling although it affects the overall QoS performance of users as well as the achievable total cell goodput. The primary goal of this paper is to compare the performance of maximum total goodput including the average delay for UGS (Unsolicited Grant Service) users employing channel-aware and queue-aware downlink schedulers for a group of users. The paper initially considers the goodput behaviour and its peak across different modulation and coding schemes for SISO and MIMO (both Space Time Block Code (STBC) and Spatial Multiplexing (SM)) connections for a single user. The achievable maximum goodput is shown to be between 94.5% and 97.0% of the theoretical data rates. The analysis is then expanded to multiple users considering Proportional Fair (PF) with different observation window, t c , Greedy and also Weighted Fair Queuing (WFQ) schedulers to serve downlink QoS flows. The PF with a higher t c = 50K exceptionally outperforms WFQ as well as the PF with a smaller t c = 500 for a higher number of users and shows a greedy like performance. The channelaware scheduler generally performs better than the queueaware scheduler.
“…However, for 50 users, it is observed that WFQ and PF, t c = 500, experience longer delay of 2s at the cost of facilitating fairness among users. On the contrary, the PF with t c =50K achieves lower delay of approximately 1s, whilst the Greedy scheduler achieves the lowest delay as agrees in [14] for a greedy type of scheduler serving VOIP. The trade-off of a greedy scheduler is that it sacrifices the fairness among users though it has the lowest delay from all the simulated schedulers in our scenario.…”
Section: B Multiple Sss and Downlink Scheduling Analysismentioning
Abstract-WiMAX performance evaluation considering different scheduling techniques has received considerable attention by WiMAX researchers and also WiMAX operators. The standard does not define MAC scheduling although it affects the overall QoS performance of users as well as the achievable total cell goodput. The primary goal of this paper is to compare the performance of maximum total goodput including the average delay for UGS (Unsolicited Grant Service) users employing channel-aware and queue-aware downlink schedulers for a group of users. The paper initially considers the goodput behaviour and its peak across different modulation and coding schemes for SISO and MIMO (both Space Time Block Code (STBC) and Spatial Multiplexing (SM)) connections for a single user. The achievable maximum goodput is shown to be between 94.5% and 97.0% of the theoretical data rates. The analysis is then expanded to multiple users considering Proportional Fair (PF) with different observation window, t c , Greedy and also Weighted Fair Queuing (WFQ) schedulers to serve downlink QoS flows. The PF with a higher t c = 50K exceptionally outperforms WFQ as well as the PF with a smaller t c = 500 for a higher number of users and shows a greedy like performance. The channelaware scheduler generally performs better than the queueaware scheduler.
“…The maximum rate scheduling is effective to advance the overall system throughput as it allocates resources to users with relatively good channel qualities among them [27]. On the other hand, the PF scheduling can improve the fairness of channel utilization among users as it distributes resources among them with consideration of their previous records of utilization [28][29][30].…”
The article presents a dynamic connection admission control (CAC) and bandwidth reservation (BR) scheme for IEEE 802.16e Broadband Wireless Access networks to simultaneously improve the utilization efficiency of network resources and guarantee QoS for admitted connections. The proposed CAC algorithm dynamically determines the admission criteria according to network loads and adopts an adaptive QoS strategy to improve the utilization efficiency of network resources. After new or handoff connections enter the networks based on current admission criteria, the proposed adaptive BR scheme adjusts the amount of reserved bandwidth for handoffs according to the arrival distributions of new and handoff connections in order to increase the admission opportunities of new connections and provide handoff QoS as well. We conduct simulations to compare the performance of our proposed CAC algorithm and BR scheme with that of other approaches. The results illustrate that our approach can effectively improve the network efficiency in terms of granting more connections by as large as about 22% in comparison with other schemes, and can also guarantee adaptive QoS for admitted new and handoff connections.
“…The relative strength scheduling algorithm (RSSA) proposed in [15], gives enhanced scheduling priority of weak users on their strong PRBs, resulting in a more equally distributed resource allocation process across an OFDM symbol via variation of tuning parameter.…”
This paper presents a detailed analysis of computational complexity, RF and operational energy consumption of a number of radio resource management strategies. Those scheduling algorithms are evaluated within a LTE downlink simulator and the results show that the adaptive scheduling algorithm is able to achieve a significant energy saving -up to average operational energy reduction gain of 71.75% and 47.86% over a conventional nonenergy aware resource allocation scheme in the pessimistic and optimistic case, respectively. In addition, the computational complexity of the algorithm is estimated, and the trade-off between RF and DSP processing for power efficiency is evaluated.
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