基于自适应LLR限幅的复杂度调整软输出球形译码
Complexity Adjusted Soft-Output Sphere Decoding by Adaptive LLR Clipping
摘要：
在多输入多输出信道上操作的后验概率（APP）接收机以增加的复杂度为代价提供增强的比特出错率（BER）性能。然而，在有利的传输环境中采用完全APP处理导致不必要的处理，其中效率较低的方法可能已经以降低的复杂度提供了所需的性能。对于缓慢变化的信道统计，可以通过简单的自适应方案实现大量的复杂性节省。这种方案通过自适应地设置相关的对数似然比（LLR）限幅值来跟踪BER性能并调整软输出球形解码器的复杂度。
英文摘要：
A-posteriori probability (APP) receivers operating over multiple-input, multiple-output channels provide enhanced bit error rate (BER) performance at the cost of increased complexity. However, employing full APP processing over favorable transmission environments, where less efficient approaches may already provide the required performance at a reduced complexity, results in unnecessary processing. For slowly varying channel statistics substantial complexity savings can be achieved by simple adaptive schemes. Such schemes track the BER performance and adjust the complexity of the soft output sphere decoder by adaptively setting the related log-likelihood ratio (LLR) clipping value.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
