中文摘要：

基于广义奇异值分解（GSVD）的信漏噪比（SLNR）预编码算法可提高传统SLNR预编码算法的数值稳定性,但其预编码器的产生需要进行奇异值分解,因此计算复杂度较高.针对这一问题,基于Fukunaga-Koontz（FK）变换方法,提出了基于SLNR的预编码算法.该算法同样具有数值稳定的优点,但无需进行奇异值分解,因此比基于GSVD的SLNR算法具有更低的计算复杂度.理论分析证明,提出的预编码算法与基于GSVD的SLNR预编码算法二者等效,验证了提出算法良好的数值稳定性;同时其复杂度较基于GSVD的预编码算法降低了34.3%～42%,因此更适合实际应用.数值仿真证明了提出算法的有效性及高效性.

英文摘要：

This signal to leakage and noise ratio（SLNR） based precoding algorithm using generalized singular value decomposition（GSVD） outperforms conventional SLNR based precoding algorithm in terms of numerical stability,but its computational complexity has proved to be high due to the necessary singular value decomposition（SVD） operation in the generation of precoder.In order to tackle this problem,a novel SLNR comprising of a precoding algorithm has proposed utilizing the Fukunaga-Koontz（FK） transform.The proposed algorithm also has the advantage of numerical stability,but without SVD operation,consequently lower computational complexity was discovered as to that of SLNR based precoding using GSVD.Theoretical analysis display the numerical stability of the proposed precoding by showing equivalency to the SLNR based precoding using GSVD.Meanwhile,the complexity was lower than the GSVD based precoding algorithm by a factor of 34.3%~42%,which makes the proposed precoding algorithm more suitable for practical implementation.Simulation results also demonstrate effectiveness and efficiency of the proposed precoding algorithm.