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For the current generation of cellular communication systems, long‐term evolution (LTE) has been the major protocol to support high‐speed data transmission. It is critical to allocate downlink spectral resource in LTE, namely, resource blocks (RBs), but the issue is not well addressed in the standard. Therefore, the paper develops an efficient RB allocation algorithm with 4 mechanisms to improve both fairness and throughput in LTE. For fairness concern, our RB allocation algorithm uses a resource‐reservation mechanism to prevent cell‐edge user equipments from starvation, and a credit‐driven mechanism to keep track of the amount of resource given to each user equipment. For throughput concern, it adopts both weight‐assignment and RB‐matching mechanisms to allocate each RB to a packet according to its flow type and length. Through simulations, we demonstrate that the proposed RB allocation algorithm can significantly increase both throughput and fairness while reducing packet dropping and delays of real‐time flows, as compared with previous methods. 相似文献
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This paper presents a model based on Queueing Theory for Orthogonal Frequency‐Division Multiplexing–Time‐Division Multiple Access (OFDM–TDMA) networks. This network model requires a Markovian model to the traffic processes. Thus, we present a Markov Modulated Fluid Model (MMFM) with autocorrelation function fitting for the network traffic, in order to evaluate the performance of the transmission link in OFDM–TDMA systems. That is, we deduce equations for estimating QoS parameters of OFDM–TDMA systems. The obtained results confirm that the proposed network model is efficient in describing the OFDM based link performance. A novel equation is also introduced for estimating the buffer overflow probability in OFDM–TDMA systems using a proposed network service curve. The computational effort is reduced compared to the Queueing Theory based method of overflow probability estimation. Besides, the results show that the estimates are very close to those obtained by simulations. 相似文献