Resource Allocation For Ofdma Systems
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Resource Allocation for OFDMA Systems
This book introduces the sources and historic collection campaigns of resource allocation in wireless communication systems. The unique characteristics of MIMO-OFDMA systems are thoroughly studied and summarized. Remarks on resource allocation and spectrum sharing are also presented, which demonstrate the great value of resource allocation techniques, but also introduce distinct challenges of resource allocation in MIMO-OFDMA systems. Novel resource allocation techniques for OFDMA Systems are surveyed from various applications (e.g., for unicast, or multicast with Guaranteed BER and Rate, subcarrier and power allocation with various detectors, low-complexity energyefficient resource allocation, etc.) in this book. Due to the high mobility and low latency requirements of 5G wireless communications, this book discusses how to deal with the imperfect CSI. It also discusses how to deal with e.g., throughput maximization, outage probabilities maximization and guarantee, energy efficiency, physical-layer security issues with feedback channel capacity constraints, in order to characterize and understand the applications of practical scenes. This book will target professionals & researchers working in the fields of Wireless Communications and Networking, Resource Allocation and Transmissions. Advanced-level students in electrical engineering and computer science will also find this book useful as a secondary textbook.
Resource Allocation for OFDMA Systems
This book introduces the sources and historic collection campaigns of resource allocation in wireless communication systems. The unique characteristics of MIMO-OFDMA systems are thoroughly studied and summarized. Remarks on resource allocation and spectrum sharing are also presented, which demonstrate the great value of resource allocation techniques, but also introduce distinct challenges of resource allocation in MIMO-OFDMA systems. Novel resource allocation techniques for OFDMA Systems are surveyed from various applications (e.g., for unicast, or multicast with Guaranteed BER and Rate, subcarrier and power allocation with various detectors, low-complexity energyefficient resource allocation, etc.) in this book. Due to the high mobility and low latency requirements of 5G wireless communications, this book discusses how to deal with the imperfect CSI. It also discusses how to deal with e.g., throughput maximization, outage probabilities maximizationand guarantee, energy efficiency, physical-layer security issues with feedback channel capacity constraints, in order to characterize and understand the applications of practical scenes. This book will target professionals & researchers working in the fields of Wireless Communications and Networking, Resource Allocation and Transmissions. Advanced-level students in electrical engineering and computer science will also find this book useful as a secondary textbook.
Optimal Chunk-based Resource Allocation for OFDMA Systems with Mulitple BER Requirements
In wireless orthogonal frequency division multiple-access (OFDMA) standards, subcarriers are grouped into chunks and a chunk of subcarriers is made as the minimum allocation unit for subcarrier allocation. We investigate the chunk-based resource allocation for OFDMA downlink, where data streams contain packets with diverse bit-errorrate (BER) requirements. Supposing that adaptive transmissions are based on a number of discrete modulation and coding modes, we derive the optimal resource allocation scheme that maximizes the weighted sum of average user rates under the multiple BER and total power constraints. With proper formulation, the relevant optimization problem is cast as an integer linear program (ILP). We can rigorously prove that the zero duality gap holds for the formulated ILP and its dual problem. Furthermore, it is shown that the optimal strategy for this problem can be obtained through Lagrange dual-based gradient iterations with fast convergence and low computational complexity per iteration. Relying on the stochastic optimization tools, we further develop a novel on-line algorithm capable of dynamically learning the underlying channel distribution and asymptotically approaching the optimal strategy without knowledge of intended wireless channels a priori. In addition, we extend the proposed approach to maximizing the a-fair utility functions of average user rates, and show that such a utility maximization can nicely balance the trade-off between the total throughput and fairness among users. Likewise, the optimal solution for the primal problem can be yielded through solving its dual problem. Numerical results are provided to gauge the performance of the proposed schemes and attain our benchmarks, followed by conclusions and later on the discussion of future directions in this field.