Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: A cross-layer resource allocation scheme for spatial multiplexing-based MIMO-OFDMA systems | Akbudak et al. EURASIP Journal on Wireless Communications and Networking 2011 2011 67 EURASIP Journal on . http content 20ii i 67 Wireless Communications and Networking a SpringerOpen Journal RESEARCH Open Access A cross-layer resource allocation scheme for spatial multiplexing-based MIMO-OFDMA systems Tarik Akbudak1 Hussein Al-Shatri2 and Andreas Czylwik1 Abstract We investigate the resource allocation problem for the downlink of a multiple-input multiple-output orthogonal frequency division multiple access MIMO-OFDMA system. The sum rate maximization itself cannot cope with fairness among users. Hence we address this problem in the context of the utility-based resource allocation presented in earlier papers. This resource allocation method allows to enhance the efficiency and guarantee fairness among users by exploiting multiuser diversity frequency diversity as well as time diversity. In this paper we treat the overall utility as the quality of service indicator and design utility functions with respect to the average transmission rate in order to simultaneously provide two services real-time and best-effort. Since the optimal solutions are extremely computationally complex to obtain we propose a suboptimal joint subchannel and power control algorithm that converges very fast and simplifies the MIMO resource allocation problem into a single-input single-output resource allocation problem. Simulation results indicate that using the proposed method achieves near-optimum solutions and the available resources are distributed more fairly among users. Keywords Cross-layer optimization Utility-based resource allocation MIMO-OFDMA Water-filling I Introduction Exploiting the channel variation across users channel-aware resource allocation can substantially improve network performance through multiuser diversity 1 . The key idea is to select those users having the best channel condition at each individual subchannel independently. This maximizes .
