使用软件计算技术的自适应通信

Atta-ur-Rahman, I. Qureshi, M. Salam, M. Z. Muzaffar
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引用次数: 2

摘要

自适应通信以其提高通信速率和环境感知的特点得到了各个通信系统的广泛关注。根据信道状态信息自适应选择不同的传输参数,如发射功率、前向纠错码率和调制方案。因此,选择一组传输参数,使信道容量最大化,并满足功率和误码率约束。寻找上述参数的最优值是一个高度非线性的问题,具有巨大的搜索空间。本文研究了蚁群算法(ACO)与模糊规则库系统(SA-FRBS)在正交频分复用环境下的自适应编码、调制和功率问题。将该方案与模拟退火和FRBS (SA-FRBS)辅助自适应编码调制和功率方案以及固定功率方案进行了比较。仿真结果表明了该方案的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive communication using softcomputing techniques
Adaptive communication has gained attention of almost every recent communication system because of its rate enhancement and context aware features. In this concept, different transmission parameters like transmit power, forward error correcting (FEC) code rate and modulation scheme are adaptively chosen according to the channel state information. Consequently, that set of transmission parameters is chosen that maximizes the channel capacity as well as fulfills the power and bit error rate constraints. Finding the optimum value of the said parameters is a highly non-linear problem with huge search space for solution. In this paper, we have investigated Ant Colony Optimization (ACO) in conjunction with a fuzzy rule base system (SA-FRBS) for adaptive coding, modulation and power in an orthogonal frequency division multiplexing environment. Proposed scheme is compared with Simulated Annealing and FRBS (SA-FRBS) assisted adaptive coding modulation and power scheme as well as with the fixed power scheme. Superiority of proposed scheme is shown by the simulations.
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