Proportional fair scheduling (PFS) provides good balance between throughput and fairness via multi-user diversity and game-theoretic equilibrium. Very little analytical work exists on understanding the performance of ...
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ISBN:
(纸本)9781424423248
Proportional fair scheduling (PFS) provides good balance between throughput and fairness via multi-user diversity and game-theoretic equilibrium. Very little analytical work exists on understanding the performance of PFS. Moreover, most researches on PFS are for cellular networks and typically use linear rate model or logarithm rate model to simplify the theoretical analysis of PFS. Since the linear rate model only applies to very small SINR, most researchers prefer the logarithm rate model in their study on PFS. While previous work which is based on the logarithm rate model provides good estimate of the PFS throughput in Rayleigh fading single-antenna cellular networks, they are not valid for multi-antenna wireless mesh networks. In this paper, PFS in multi-antenna wireless mesh networks under Rayleigh fading is discussed. Specifically, we assume that orthogonal frequency-division multiplexing (OFDM) and single-input multi-output (SIMO) techniques are used in the network. In addition, a new mathematical analysis of PFS that applies to both Rayleigh and Rician fading is presented. Simulations are conducted to verify our analytic results on PFS in the proposed mesh network. To the best of our knowledge, this work is the first one investigating the PFS problem in multi-antenna mesh networks.
This paper investigates a blind space-time equaliser (STE) designed for single-input multiple-output (SIMO) systems that employ high-throughput quadrature amplitude modulation schemes. A constant modulus algorithm (CM...
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This paper investigates a blind space-time equaliser (STE) designed for single-input multiple-output (SIMO) systems that employ high-throughput quadrature amplitude modulation schemes. A constant modulus algorithm (CMA) aided soft decision-directed (SDD) scheme, originally derived for low-complexity blind equalisation of single-inputsingle-output channels, is extended to the SIMO scenario. Simulations are conducted to compare the performance of this blind adaptive scheme with another low-complexity blind STE referred to as the CMA aided decision directed (DD) scheme. The results obtained demonstrate that for SIMO systems the CMA aided SDD scheme exhibits advantages over the CMA aided DD arragement, in terms of its faster convergence speed and lower computational complexity.(c) 2007 Elsevier B.V. All rights reserved.
In this paper, a power-based channel identification method is investigated based on the Cross-relations (CR) subspace of SIMO channels. The proposed method remains in stable condition and reduces the computational bur...
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In this paper, a power-based channel identification method is investigated based on the Cross-relations (CR) subspace of SIMO channels. The proposed method remains in stable condition and reduces the computational burden due to avoiding matrix inversion and joint square matrix multiplication. Compared to the Mul-tichannel least mean squared (MCLMS) method, it owns a faster convergence rate and the higher estimation accuracy with a close complexity. Furthermore, its performance is the same as the Cross-relations subspace iterations with Inversion (CRSI-INV) method and exceeds that of the Multichannel Newton (MCN) method in case of sufficient data samples, but with a lower complexity. Besides, a comparative study on channel identification methods is proposed and analyzed with respect to convergence rate and computational complexity. Simulations are also provided for demonstrating the superior performance of the proposed scheme.
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