基于排序方差的非参量自动删除检测算法

为了增强广义符号(GS)检测算法在多目标环境中的检测性能,基于自动删除单元平均(AC-CA)检测算法和GS统计量提出了一种新的非参量检测算法(ACGS),它的前沿和后沿均采用ACCA检测算法进行参考单元选择,然后与检测单元进行比较形成检验统计量.分别针对均匀背景和多目标环境分析了ACGS检测算法的性能,并与GS检测算法进行了比较,最后利用实测数据进行验证.结果表明在均匀杂波背景下,ACGS检测算法较GS检测算法有较小的CFAR损失,但在多目标背景下较GS检测算法取得了较大的性能改善.     

基于消息传递的大规模多用户MIMO低复杂度的检测算法

针对大规模多用户多输入多输出(MIMO)系统中基站端检测复杂度高的问题,提出了一种低复杂度、基于强制收敛的变量节点全信息高斯消息传播迭代检测(VFI-GMPID-FC)算法.首先对传统的GMPID算法进行改进,得到VFI-GMPID算法,VFI-GMPID算法的检测性能逼近最小均方误差检测(MMSE)算法,但复杂度要大大低于MMSE算法.然后结合强制收敛思想和VFI-GMPID,提出VFI-GMPID-FC算法,进一步降低算法复杂度,提升检测效率.最后通过仿真结果表明,所提算法在保证检测性能的同时,能有效地降低算法的复杂度.     

基于FB-CFAR的多径信道阶检测算法

多径信道阶的检测是无线通信参数化信道估计的首要步骤,对系统性能有着重要的影响.然而,目前使用的检测方法大多是基于Akaike信息理论准则(AIC)或最小描述长度准则(MDL)提出的.这些准则在高信噪比条件下性能较好,但在低信噪比时检测性能不好.本文提出了一种基于前后平滑恒虚警率准则(FB-CFAR)的算法来提高信道阶的检测性能.OFDM系统中的仿真结果表明该算法能有效提高低信噪比时多径信道阶的正确检测概率.     

Khatri-Rao积变换下的离格信号DOA估计

当存在离格信号时,基于稀疏表示的波达角(DOA)估计算法性能损失严重.为解决这个问题,在对接收数据协方差矩阵进行Khatri-Rao积变换的基础上,推导了离格信号网格偏离量与紧邻信号原子系数之间的关系,提出了一种单一离格信号DOA估计方法.为提高对邻近离格信号DOA的估计性能,利用矩阵的广义逆性质提出了基于多原子系数的联合估计方法.仿真实验表明,单一离格信号DOA估计方法在低信噪比下有较好的性能,联合估计方法在高信噪比条件下对邻近离格信号DOA有较高的估计精度,同时所提算法估计性能几乎不受网格划分间距的影响,可以通过增大网格间距降低算法运算量.相关研究对阵列天线DOA估计具有一定的参考价值.     

一种基于检测统计量的SOSGO-CFAR 检测算法

提出了一种新的恒虚警检测算法SOSGO-CFAR.该算法应用检测单元采样作为选择参考单元的依据,使用了基于转换恒虚警(S-CFAR)和排序选大恒虚警(OSGO-CFAR)的复合算法.文章给出了该算法在均匀背景中的数学分析.并在均匀背景、杂波边缘和多目标情况下,用MonteCarlo方法进行了仿真分析.结果表明,该检测器既具有均匀背景下和CA-CFAR相近的良好性能,在杂波边缘环境中,具有接近OSGO-CFAR的性能,且在多目标环境中,其性能明显好于S-CFAR.     

一种稳健的室内无模糊多声源TDOA估计算法

该文针对室内环境下的宽间距多声源到达时间差(TDOA)估计问题,研究了一种基于近似核密度估计(KDE)的无模糊算法。根据声频信号的短时频谱稀疏性,利用相关性检测(CT)提取单个声源能量占优的时频支撑域,进而将观测信号的归一化互功率谱(NCS)所构建的近似核函数通过累加平均削弱室内混响的干扰,同时引入多阶段(MS)分频带处理有效解决宽间距时的空域模糊。理论推导及仿真研究验证了该算法是一种稳健的室内无模糊多声源TDOA估计算法。     

一种基于ML算法及盲信道识别的DWPM系统

该文提出了一种基于ML算法及盲信道估计的离散小波包调制(Discrete Wavelet Packet Modulation,DWPM)系统.本文通过基于导频信号的盲信道识别方法,获得信道的状态信息,并且利用基于ZF(Zero Forcing)算法的H矩阵消除码间干扰,最后,利用ML(Maximum Likelihood)算法检测解调后的码元,并且通过仿真分析了该系统在多径衰落信道下的性能.仿真结果表明,该系统的性能要比传统的OFDM系统的性能好.     

稀疏码分多址系统一种改进的检测算法

稀疏码分多址(SCMA)系统中基于球形译码算法(SD)由于具有优良的性能受到越来越多的关注,然而现有基于SD的算法只能用于某些特定星座结构的检测,导致其应用受限.该文提出一种适用于任意星座且性能达到最大似然(ML)算法性能的改进球形译码(ISD)算法.该算法将用户星座图拆分,并将用户星座图转换为多层树结构,利用对树结构的搜索完成译码操作,并且对树的搜索是从高层向低层进行的.因此,可以将SCMA检测转换成最小化树结构部分度量问题;同时,所提出的改进算法对星座图的结构无任何限制,所以该算法适用于任意类型的星座图.此外,由于SCMA的稀疏性,每一层的部分度量均与分配给每个资源元素的用户无关,从而进一步降低了计算复杂度.     

基于互Wigner-Ville分布的SAR运动目标检测

本文针对机载合成孔径雷达(SAR)运动目标回波信号的特点,提出了基于互Wigner-Ville分布(XWVD)的机载SAR运动目标检测方法,分析了它在单目标和多目标情况下的检测性能.实验证明,该方法可以在较低的信噪比下实现目标的检测,其性能大大优于常用的Wigner-Ville分布方法.为了抑制多个目标之间交叉项的影响,本文还提出了一种基于逐次消去思想的互Wigner-Ville分布检测方法,它可以解决强度相差较大的多目标检测问题.仿真实验的结果证明了算法的有效性.     

广义空间调制系统的低复杂度检测算法

针对广义空间调制( GSM)系统接收端最大似然( ML)检测算法计算复杂度极高的缺点,提出了一种基于压缩感知( CS)信号重构理论的低复杂度信号检测算法。首先,在多输入多输出( MI-MO)信道模型下,通过改进正交匹配追踪( OMP)算法,得到一个激活天线索引备选集;然后,利用ML算法在该备选集中进行遍历搜索,检测出激活天线索引和星座调制符号。仿真结果表明所提算法的检测性能接近于ML算法,且复杂度约为ML算法的2%。因此,所提算法在保证检测性能的同时也大大降低了计算复杂度,实现了检测性能与复杂度之间的平衡。     

Hybrid iterative multiuser detection for channel coded space division multiple access OFDM systems

Space division multiple access (SDMA) aided orthogonal frequency division multiplexing (OFDM) systems assisted by efficient multiuser detection (MUD) techniques have recently attracted intensive research interests. The maximum likelihood detection (MLD) arrangement was found to attain the best performance, although this was achieved at the cost of a computational complexity, which increases exponentially both with the number of users and with the number of bits per symbol transmitted by higher order modulation schemes. By contrast, the minimum mean-square error (MMSE) SDMA-MUD exhibits a lower complexity at the cost of a performance loss. Forward error correction (FEC) schemes such as, for example, turbo trellis coded modulation (TTCM), may be efficiently combined with SDMA-OFDM systems for the sake of improving the achievable performance. Genetic algorithm (GA) based multiuser detection techniques have been shown to provide a good performance in MUD-aided code division multiple access (CDMA) systems. In this contribution, a GA-aided MMSE MUD is proposed for employment in a TTCM-assisted SDMA-OFDM system, which is capable of achieving a similar performance to that attained by its optimum MLD-aided counterpart at a significantly lower complexity, especially at high user loads. Moreover, when the proposed biased Q-function based mutation (BQM) assisted iterative GA (IGA) MUD is employed, the GA-aided system's performance can be further improved, for example, by reducing the bit error ratio (BER) measured at 3 dB by about five orders of magnitude in comparison to the TTCM-assisted MMSE-SDMA-OFDM benchmarker system, while still maintaining modest complexity.     

Multistage MMSE PIC Space–Time Receiver With Non-Mutually Exclusive Grouping

The arrival of new data services for wireless mobile communications requires an efficient use of the available bandwidth. Interference-limited cellular systems based on code-division multiple access (CDMA) can benefit from multiuser detection (MUD) and beamforming with antenna array to reduce multiple-access interference. Group-based techniques have been proposed to reduce the complexity of space-time MUD and have been shown to provide a performance-complexity tradeoff between matched filtering and full MUD. In this paper, the intergroup interference, which is a limiting factor in group-based systems, is reduced using multistage parallel interference cancellation after group-based minimum mean square error (MMSE) linear filtering. In addition, the extra resources that are available at the receiver are exploited by sharing users among groups. The proposed receiver is shown to converge, as the number of stages increases, to the full space-time MMSE linear MUD filter. The results show that the new approach provides bit error rate (BER) performance close to the full MUD receiver at a fraction of the complexity.     

MBER Space-Time Decision Feedback Equalization Assisted Multiuser Detection for Multiple Antenna Aided SDMA Systems

This paper proposes a space-time decision feedback equalization (ST-DFE) assisted multiuser detection (MUD) scheme for multiple receiver antenna aided space division multiple access systems. A minimum bit error rate (MBER) design is invoked for the MUD, which is shown to be capable of improving the achievable bit error rate performance and enhancing the attainable system capacity over that of the standard minimum mean square error (MMSE) design. An adaptive implementation of the MBER ST-DFE assisted MUD is proposed using a stochastic gradient-based least bit error rate algorithm, which is demonstrated to consistently outperform the classical least mean square (LMS) algorithm, while achieving a lower computational complexity than the LMS algorithm for the binary signalling scheme. Our simulation results demonstrate that the MBER ST-DFE assisted MUD is more robust to channel estimation errors as well as to potential error propagation imposed by decision feedback errors, compared to the MMSE ST-DFE assisted MUD.     

Multiuser Detection in SDMA–OFDM Wireless Communication System Using Complex Multilayer Perceptron Neural Network

The space division multiple access–orthogonal frequency division multiplexing (SDMA–OFDM) wireless system has become very popular owing high spectral efficiency and high load capability. The optimal maximum likelihood multiuser detection (MUD) technique suffers from high computational complexity. On the other hand the linear minimum mean square error (MMSE) MUD techniques yields poor performance and also fails to detect users in overload scenario, where the number of users are more than that of number of receiving antennas. By contrast, the differential evolution algorithm (DEA) aided minimum symbol error rate (MSER) MUD can sustain in overload scenario as it can directly minimizes probability of error rather than mean square error. However, all these classical techniques are still complex as these do channel estimation and multiuser detection sequentially. In this paper, complex multi layer perceptron (CMLP) neural network model is suggested for MUD in SDMA–OFDM system as it do both channel approximation and MUD simultaneously. Simulation results prove that the CMLP aided MUD performs better than the MMSE and MSER techniques in terms of enhanced bit error rate performance with low computational complexity.     

BER analysis of the optimum multiuser detection with channel mismatch in MC-CDMA systems

In this paper, we analyze the bit-error-rate (BER) performance of the optimum multiuser detection (MUD) with channel mismatch in multicarrier code-division-multiple-access (MC-CDMA) systems. The BER performance of the optimum MUD without channel mismatch in MC-CDMA systems has been recently derived using the replica method. However, it is left unjustified, since the replica method is not a rigorous approach. In addition, it is NP-hard to implement an optimum MUD algorithm. To justify the BER performance and to make the optimum MUD feasible, based on Pearl's belief propagation (BP) scheme, we put together a low-complexity iterative MUD algorithm for MC-CDMA systems. Furthermore, channel mismatch is introduced into the BP-based MUD algorithm to make the scenario general. With channel mismatch, the analytical results of the BP-based MUD algorithm conform perfectly to, and the simulation results of the BP-based MUD algorithm conform very closely to the BER performance of the optimum MUD derived using the replica method, which is a nontrivial extension of the existing replica approach mentioned above. Without channel mismatch, the problem becomes a special case of our contribution.     

Hybrid SNR-Adaptive Multiuser Detectors for SDMA-OFDM Systems

Multiuser detection (MUD) and channel estimation techniques in space-division multiple-access aided orthogonal frequency-division multiplexing systems recently has received intensive interest in receiver design technologies. The maximum likelihood (ML) MUD that provides optimal performance has the cost of a dramatically increased computational complexity. The minimum mean-squared error (MMSE) MUD exhibits poor performance, although it achieves lower computational complexity. With almost the same complexity, an MMSE with successive interference cancellation (SIC) scheme achieves a better bit error rate performance than a linear MMSE multiuser detector. In this paper, hybrid ML-MMSE with SIC adaptive multiuser detection based on the joint channel estimation method is suggested for signal detection. The simulation results show that the proposed method achieves good performance close to the optimal ML performance at low SNR values and a low computational complexity at high SNR values.     

Multiple-antenna-aided OFDM employing genetic-algorithm-assisted minimum bit error rate multiuser detection

The family of minimum bit error rate (MBER) multiuser detectors (MUD) is capable of outperforming the classic minimum mean-squared error (MMSE) MUD in terms of the achievable bit-error rate (BER) owing to directly minimizing the BER cost function. In this paper, we will invoke genetic algorithms (GAs) for finding the optimum weight vectors of the MBER MUD in the context of multiple-antenna-aided multiuser orthogonal frequency division multiplexing (OFDM) . We will also show that the MBER MUD is capable of supporting more users than the number of receiver antennas available, while outperforming the MMSE MUD.     

An Adaptive Multiuser Detection Algorithm for CDMA Systems Using Antenna Diversity

Based on the minimum mean squared error (MMSE) between the data stream and the linear combiner output, a new multiuser detection (MUD) algorithm that combines space–time (ST) processing and antenna array on direct-sequence CDMA signals is proposed. The proposed ST-MUD algorithm is proved to be equivalent to two existing MMSE-based ST-MUD algorithms, and the theoretical BER performances for all the three algorithms are the same. The most attractive feature of the new ST-MUD algorithm is based on the fact that the new method does not require explicit estimation of channel and signaling information. This avoids any channel estimation error, and the method is thus more robust and more accurate than the other two ST-MUD algorithms in practical implementation. Adaptation of the proposed ST-MUD algorithm is implemented by using training sequences. Performance of this new multiuser detector is compared with that of two existing MMSE multiuser detectors and the conventional single-user space–time rake receiver through simulations. The proposed ST-MUD algorithm provides a performance better than existing algorithms and is especially suitable for practical CDMA systems.     

On the usefulness of outer-loop power control with successive interference cancellation

Multiuser detection (MUD) performance can be significantly better than the conventional matched filter receiver in CDMA systems. Further, since optimal MUD is exponentially complex, research has mainly focused on suboptimal approaches such as successive interference cancellation (SIC). SIC requires a geometric distribution of received powers to achieve equal performance for all received signals. We propose a power control scheme for SIC to achieve this profile (or the profile corresponding to any desired and achievable set of error rates) based on frame-error rate (FER) or bit-error rate (BER). Specifically, we derive the relationship between received power and BER for linear SIC and show that for unlimited mobile powers, a deterministic distributed BER-based outer-loop power control drives the received powers to the optimal power profile. The convergence of the deterministic BER-based algorithm is examined in the absence of inner loop power control errors. The simulated performance of a stochastic version of this algorithm is examined using instantaneous FER measurements. The stochastic algorithm is shown to provide unbiased estimates of the true power updates and converge to the optimal power vector provided the mobiles have unlimited power. We consider power limits for specific mobiles and find that individual mobile limits do not affect the performance of other signals. We examine the impact of system loading, multiple FER targets, error correction, and inner loop power control error on the performance of the algorithm.     

Reliability feedback–aided low‐complexity detection in uplink massive MIMO systems

Massive multiple‐input multiple‐output (MIMO) plays a crucial role in realizing the demand for higher data rates and improved quality of service for 5G and beyond communication systems. Reliable detection of transmitted information bits from all the users is one of the challenging tasks for practical implementation of massive‐MIMO systems. The conventional linear detectors such as zero forcing (ZF) and minimum mean square error (MMSE) achieve near‐optimal bit error rate (BER) performance. However, ZF and MMSE require large dimensional matrix inversion which induces high computational complexity for symbol detection in such systems. This motivates for devising alternate low‐complexity near‐optimal detection algorithms for uplink massive‐MIMO systems. In this work, we propose an ordered sequential detection algorithm that exploits the concept of reliability feedback for achieving near‐optimal performance in uplink massive‐MIMO systems. In the proposed algorithm, symbol corresponding to each user is detected in an ordered sequence by canceling the interference from all the other users, followed by reliability feedback‐based decision. Incorporation of the sequence ordering and the reliability feedback‐based decision enhances the interference cancellation, which reduces the error propagation in sequential detection, and thus, improves the BER performance. Simulation results show that the proposed algorithm significantly outperforms recently reported massive‐MIMO detection techniques in terms of BER performance. In addition, the computational complexity of the proposed algorithm is substantially lower than that of the existing algorithms for the same BER. This indicates that the proposed algorithm exhibits a desirable trade‐off between the complexity and the performance for massive‐MIMO systems.