共查询到17条相似文献,搜索用时 218 毫秒
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现有的空间调制系统球形译码(Sphere-Decoding,SD)检测算法虽然能够较大地降低最大似然(Maximum-Likelihood,ML)检测算法的计算复杂度,但由于其更新半径比较松散、收敛较慢,计算复杂度降低的水平仍十分有限,尤其是在高阶调制系统下.针对上述问题,采用统计分布的思想对现有算法更新半径中的冗余项进行估计,提出了两种改进的球形译码检测算法.理论分析与仿真结果表明,改进算法在达到最优检测性能的同时,极大地降低了传统球形译码的计算复杂度,具有较好的理论和实际应用意义. 相似文献
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球形译码是多输入多输出(MIMO)系统中一种高效的检测算法。但对于非确定性MIMO系统,已有球形译码算法不能同时获得最优解和最低搜索树。针对该问题,提出了一种高效球形译码检测算法,通过增加常量对最大似然代价函数进行等价转化,使得球形译码算法获得最优解的同时具有最低搜索树,大大降低了球形译码算法中的搜索复杂度。仿真结果表明,对于高阶正交幅度调制(M-QAM,M>4)方式,本文算法优于修正的CT(Modified Cui and Tellambura,MCT)算法,大大提高了球形译码中的搜索效率。此外,仿真结果给出了最小复杂度下的最优参数值。 相似文献
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球形译码算法的检测性能最接近最大似然检测算法,但其计算复杂度仍然较高。为了在计算复杂度和系统性能之间取得良好折中,在研究标准球形译码的基础上,提出一种新的球形译码改进算法。新算法由快速球形译码与基于MMSE准则的SQRD算法构成。该算法在高信噪比时采用SQRD算法,低信噪比时采用KSDA算法。仿真结果表明,该算法在降低球形译码算法复杂度的同时获得了较好的系统性能。 相似文献
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球形译码的半径对译码的复杂度有很大的影响。文章在卡方分布特性的基础上设计了一种基于统计裁剪的改进球形译码算法,该算法通过减去估算出来的未检测层的半径的大小,达到对当前检测层的半径进行缩减的目的;同时综合考虑了信道的影响,对均方误差较大的列进行ML检测,剩余信号进行树裁剪的SD算法。仿真表明,该算法大大降低了球形译码的算法复杂度。 相似文献
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为酉空时调制系统设计的多符号差分球形译码(MSDSD)能以较低复杂度获得最大似然(ML)检测性能。但是,该算法基于准静态信道假设,当将它用于快衰落信道时会出现严重的误码平层现象。本文基于连续衰落信道假设,推导了一种ML度量的递推形式,并将其嵌入自动球形译码算法中,得到了的多符号差分自动球形译码(MSDASD)算法。该算法适用于一般酉空时星座,克服了MSDSD的误码平层现象,可达到ML检测的性能,其平均复杂度在大多数情况下低于相同假设下的判决反馈检测算法。 相似文献
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It is well known that maximum-likelihood (ML) decoding in many digital communication schemes reduces to solving an integer least-squares problem, which is NP hard in the worst-case. On the other hand, it has recently been shown that, over a wide range of dimensions N and signal-to-noise ratios (SNRs), the sphere decoding algorithm can be used to find the exact ML solution with an expected complexity that is often less than N3. However, the computational complexity of sphere decoding becomes prohibitive if the SNR is too low and/or if the dimension of the problem is too large. In this paper, we target these two regimes and attempt to find faster algorithms by pruning the search tree beyond what is done in the standard sphere decoding algorithm. The search tree is pruned by computing lower bounds on the optimal value of the objective function as the algorithm proceeds to descend down the search tree. We observe a tradeoff between the computational complexity required to compute a lower bound and the size of the pruned tree: the more effort we spend in computing a tight lower bound, the more branches that can be eliminated in the tree. Using ideas from semidefinite program (SDP)-duality theory and Hinfin estimation theory, we propose general frameworks for computing lower bounds on integer least-squares problems. We propose two families of algorithms, one that is appropriate for large problem dimensions and binary modulation, and the other that is appropriate for moderate-size dimensions yet high-order constellations. We then show how in each case these bounds can be efficiently incorporated in the sphere decoding algorithm, often resulting in significant improvement of the expected complexity of solving the ML decoding problem, while maintaining the exact ML-performance. 相似文献
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Multiple-Input-Multiple-Output communication systems demand fast sphere decoding with high performance. To speed up the computation,
we propose a scheme with multiple fixed complexity sphere decoders to construct a parallel soft-output fixed complexity sphere
decoder (PFSD). The proposed decoder is highly parallel and has performance comparable to soft-output list fixed complexity
sphere decoder (LFSD) and K-best sphere decoder. In addition, we propose a parallel QR decomposition algorithm to lower the preprocessing overhead, and
a low complexity LLR algorithm to allow parallel update of LLR values. We demonstrate that the PFSD algorithm can increase
the throughput and reduce bit error rate of a soft-output solution in a 4 × 4 16-QAM system, and has superior performance
compared to other soft decoders with comparable throughput and computation complexity. The PFSD algorithm has been mapped
onto Xilinx XC4VLX160 FPGA. The resulting PFSD decoder can achieve up to 75 Mbps throughput for 4 × 4 64-QAM configuration
at 100MHz with low control overhead. 相似文献
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针对多输入多输出(MIMO)无线通信系统中基于球形译码算法(Sphere Decoding Algorithm,SDA)在低信噪比区域较高的复杂度,提出一种半定松弛算法和有限星座SDA相结合的信噪比自适应的SDA。通过仿真得知,所提出的算法与已有的SDA相比,在低信噪比区域有较低的算法复杂度,并且误比特性能逼近于最优的SDA。 相似文献
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In this article, a new system model for sphere decoding (SD) algorithm is introduced. For the 2 × 2 multipleinput multiple-out (MIMO) system, a simplified maximum likelihood (SML) decoding algorithm is proposed based on the new model. The SML algorithm achieves optimal maximum likelihood (ML) performance, and drastically reduces the complexity as compared to the conventional SD algorithm. The improved algorithm is presented by combining the sphere decoding algorithm based on Schnorr-Euchner strategy (SE-SD) with the SML algorithm when the number of transmit antennas exceeds 2. Compared to conventional SD, the proposed algorithm has low complexity especially at low signal to noise ratio (SNR). It is shown by simulation that the proposed algorithm has performance very close to conventional SD. 相似文献