摘要
为在较低复杂度的情况下提升误码率的检测性能,提出一种基于QR分解的低复杂度的可靠性约束算法。采用阴影面积约束方法判断软估计的可靠性,同时引入星座点作为候选点,从多个候选点中选出最优候选点进行反馈。仿真结果表明,与常规的QR分解算法相比,该算法只需增加较小的算法复杂度即可明显改善系统存在的干扰,并且在判决回馈中减少错误传播。同时,可以通过约束阈值的大小和候选点数量控制运算复杂度并改善算法的误码率检测性能。
The paper proposes a low-complexity reliability constraint algorithm based on QR decomposition. The algorithm judges soft estimates by shadow area constraint method. Besides, constellation points are introduced as the candidate points, and the optimal candidate point is chosen from multiple candidate points for feedback. Simulation results show that, compared with conventional QR decomposition algorithm, thealgorithm can significantly improve system interference and greatly reduce error propagation in decision-feedback, meanwhile, it can control the operation complexity and improve the detection performance of error rate.
出处
《计算机工程》
CAS
CSCD
北大核心
2017年第8期120-125,共6页
Computer Engineering
基金
国家自然科学基金(41505017)
江苏省气象探测与信息处理重点实验室开放课题(kdxs1302)
关键词
QR分解
阴影面积约束
可靠性
最优候选
算法复杂度
QR decomposition
shadow area constraint
reliability
optimal candidate
algorithm complexity
