Future communication systems will include di erent types of messages requiring di erent transmission rates,packet lengths,and service qualities.We address the power-optimization issues of communication systems conveyi...Future communication systems will include di erent types of messages requiring di erent transmission rates,packet lengths,and service qualities.We address the power-optimization issues of communication systems conveying multiple message types based on nite-delay information theory.Given both the normalized transmission rate and the packet length of a system,the actual residual decoding error rate is a function of the transmission power.We propose a generalized power allocation framework for multiple message types.Two di erent optimization cost functions are adopted:the number of service-quality violations encountered and the sum log ratio of the residual decoding error rate.We provide the optimal analytical solution for the former cost function and a heuristic solution based on a genetic algorithm for the latter one.Finally,the performance of the proposed solutions are evaluated numerically.展开更多
基金This work is supported by the National Key Basic Research Program of China(No.2013CB329201)Key Program of Na-tional Natural Science Foundation of China(No.61631018)+3 种基金Key Research Program of Frontier Sciences of CAS(No.QYZDY-SSW-JSC003)Key Project in Science and Technology of Guangdong Province(No.2014B010119001)Shenzhen Peacock Plan(No.1108170036003286)the Fundamental Research Funds for the Central Universities.
文摘Future communication systems will include di erent types of messages requiring di erent transmission rates,packet lengths,and service qualities.We address the power-optimization issues of communication systems conveying multiple message types based on nite-delay information theory.Given both the normalized transmission rate and the packet length of a system,the actual residual decoding error rate is a function of the transmission power.We propose a generalized power allocation framework for multiple message types.Two di erent optimization cost functions are adopted:the number of service-quality violations encountered and the sum log ratio of the residual decoding error rate.We provide the optimal analytical solution for the former cost function and a heuristic solution based on a genetic algorithm for the latter one.Finally,the performance of the proposed solutions are evaluated numerically.
