球形译码算法在信号空间分集系统中的应用研究

针对信号空间分集系统中最大似然检测算法复杂度高的问题，选用球形译码算法作为信号空间分集系统接收机检测算法，可以使接收机在接近最大似然算法检测性能的同时，降低接收机检测复杂度。为进一步降低检测复杂度，通过采用最小均方误差算法减小噪声对接收信号的干扰，来降低因搜索噪声点而产生的复杂度，并利用衰减因子k加快搜索半径收缩来达到进一步降低球形译码算法检测复杂度的目的。仿真结果表明，在信号空间分集系统中引入球形译码算法可以降低接收机检测复杂度，并且改进后的球形译码算法检测时间在低信噪比情况下约为传统球形译码算法的12%—33%。因此，球形译码算法可以有效地降低信号空间分集系统接收机检测复杂度。

Application of Sphere Decoding Algorithmin Signal Space Diversity System

Aiming at the problem of high complexity of the maximum likelihood detection algorithm in the signal space diversity system, sphere decoding algorithm is used as the receiver detecting algorithm, whose performance is as good as the maximum likelihood algorithm, which reduces the complexity of the receiver in signal space diversity system. The minimum mean square error algorithm is used to lower the received signal noise so as to reduce the complexity caused by the noise point searching; the algorithm complexity is further reduced by speeding up the search radius constriction with attenuation factor k, which makes receiver better. The simulation results show that sphere decoding algorithm in signal space diversity system can reduce the complexity of the receiver , and the improved sphere decoding detection time in low signal to noise ratio is about traditional sphere decoding algorithm of 12% - 33%. Therefore, the sphere decoding algorithm can reduce the receiver signal space diversity detection system complexity effectively.