空时分组编码多载波码分多址系统的直接解码

针对宏蜂窝小区中基站使用均匀线阵空时分组编码多载波码分多址系统的上行物理链路,该文提出了一种无需信道估计,直接对多个用户的发射符号和波达方向进行盲估计的算法。该算法通过构筑蕴涵用户编码符号序列和波达方向的辅助矩阵,对其进行特征分解,得到了每个用户波达方向的闭式解。进而,利用空时分组码的正交结构以及发射符号的有限码集特性给出了所有活动用户原始符号序列的闭式估计。计算机仿真实验验证了该算法的有效性。     

一种新的用于多天线系统的快速球形解码算法

本文提出了一种实现多输入—多输出(MIMO)无线系统最大似然(ML)信号检测的快速球形解码器框架,在本框架内,算法不需要确定半径参数,同时,在算法的搜索阶段只需要访问最少的树节点数,从而降低算法的复杂度。另外,当我们采用一种直接的Schnorr-Euchner枚举(SEE)方法时,本球解码框架可用于复数MIMO系统。仿真结果显示,和其它球形解码器相比,本解码器能大大提升最大似然(ML)检测的速度。     

用于病态MIMO系统的一种快速球形译码算法

如今的球形译码算法研究,多是针对MIMO系统的传输矩阵满秩的情况。然而现实常常出现传输矩阵是奇异阵的情况即传输矩阵为病态矩阵,原先的球形译码算法将不再适用。本文提出了一种快速的球形译码算法,设法将病态矩阵变为满秩矩阵,并利用迫零检测估计来对最初的半径取值加以限制,大大加快了搜索速度,而性损失却很小。     

Lattice Sphere Decoding for Data Transmission Systems with Special Channel Matrices

This paper presents the effects of condition number ( \(\tau \) ) in communication system performance. It has been shown that a small condition number ( \(\tau \) ) results a better performance. The proposed scheme is using special kind of matrices with Lattice Sphere Decoding (LSD) technique for Block Data Transmission Systems (BDTS). Hankel and Toeplitz matrices are used separately as a channel matrix (H) while circulant matrix is used in the previous works. The proposed scheme reduced the condition number ( \(\tau \) ) and, therefore, improve the system performance. As a result; LSD-based BDTS with Toeplitz/Hankel matrix outperforms the LSD-based BDTS with circulant matrix. Complexity analysis is also done which based on lattice dimension and initial radius selection.     

PSK调制下空频块码的低复杂度复数球形译码

对于PSK调制下的空频块码,复数球形译码相对实数球形译码有较低的复杂度.当复数球形译码的初始半径趋向无穷大时,排序的复杂度高.本文针对PSK符号提出每层符号以排序中心点为中心,在极坐标角度维按照之字(Zigzag)排序的方法.通过查表可以快速获得排序后的符号序列,查表排序球形译码算法相对于通用复数球形译码算法在16-PSK调制14dB平均比特信噪比下节省约61%的复杂度.     

Dynamic Nulling-and-Canceling for Efficient Near-ML Decoding of MIMO Systems

It is known that conventional nulling-and-canceling (NC) detection for multiple-input/multiple-output (MIMO) systems cannot exploit all of the available diversity, and, thus, its performance is significantly inferior to that of maximum likelihood (ML) detection. Conventional NC employs the layerwise postequalization signal-to-noise ratios (SNRs) as reliability measures for layer sorting. These SNRs are average quantities that do not depend on the received vector. In this paper, we propose the novel dynamic nulling-and-canceling (DNC) technique that uses approximate a posteriori probabilities as measures of layer reliability. The DNC technique is a minimum mean-square error (MMSE) nulling scheme combined with an improved "dynamic" layer sorting rule that exploits the information contained in the current received vector. We calculate the error probability of DNC for a simple special case and show that it is upper bounded by the error probability of conventional NC. Simulation results are presented for spatial multiplexing systems and for systems using linear dispersion codes. It is demonstrated that the DNC technique can yield near-ML performance for a wide range of system sizes and channel SNRs at a fraction of the computational complexity of the sphere-decoding algorithm for ML detection     

一种MIMO系统中的快速广义复球形解码算法

该文提出了一种广义复球形解码算法。它能处理多输入多输出系统(MIMO)中发送天线多于接收天线的情形,并能同时检测具有格型结构和不具有格型结构的二维空间星座信号。该算法对信号矢量的超定部分进行优化搜索,从而避免了穷尽搜索的高复杂度。仿真结果表明该广义复球形解码算法的复杂度明显低于采用穷尽搜索策略的复杂度。     

一种新的多天线系统中的快速广义球形解码算法

该文提出了一种新的广义球形解码算法.与常规球形解码算法相比,它能够处理多输入多输出系统(MIMO)中发送天线M多于接收天线N的情形,并且其解码速度远大于已有的广义球形解码算法.其基本思想是将M维的传输信号矢量分成N-1和M-N+1维的子矢量xa和xb,通过一些简单地变换,就可以使用一个常规球形解码器来选取合适的xb,然后再利用另一个常规球形解码器来获得xa,从而得到整个传输信号矢量.仿真结果表明,这种新的快速广义球形解码算法(命名为双层球形解码算法)比现有的广义球形解码算法具有更低的复杂度.     

衰落信道CDMA系统联合检测的球译码算法

利用穷搜索的ML联合检测,其复杂度随输入长度指数增长,因而实际系统中很难实现。球译码算法以多项式的复杂度取得接近ML的性能引起广泛的研究。提出一种用于衰落信道LAS-CDMA系统联合检测的球译码算法,与原始算法相比,该算法具有更低的复杂度,对初始半径的选择敏感性更低。在初始半径的选择足够大之后,即使对于大的调制星座,也可以在保证低复杂度的同时取得ML解,对于LAS-CDMA系统,该算法在ML的意义上是最优的。     

基于MIMO系统的球形译码算法的改进

在最大似然检测中,球形译码算法是一种有效的快速算法。提出一种基于MIMO系统的新的快速球形译码算法,它的复杂度比传统的算法要小的多。在提出的方法中,初始半径的选择并不重要。这种改进算法的译码性能和复杂度由两个参数来控制。因此,该方法存在着译码性能和复杂度的均衡。通过计算机仿真,可以看到,提出改进算法的译码性能得到了较大的提高。     

Performance Analysis of Layer Pruning on Sphere Decoding in MIMO Systems

Sphere decoding (SD) for multiple‐input and multiple‐output systems is a well‐recognized approach for achieving near‐maximum likelihood performance with reduced complexity. SD is a tree search process, whereby a large number of nodes can be searched in an effort to find an estimation of a transmitted symbol vector. In this paper, a simple and generalized approach called layer pruning is proposed to achieve complexity reduction in SD. Pruning a layer from a search process reduces the total number of nodes in a sphere search. The symbols corresponding to the pruned layer are obtained by adopting a QRM‐MLD receiver. Simulation results show that the proposed method reduces the number of nodes to be searched for decoding the transmitted symbols by maintaining negligible performance loss. The proposed technique reduces the complexity by 35% to 42% in the low and medium signal‐to‐noise ratio regime. To demonstrate the potential of our method, we compare the results with another well‐known method — namely, probabilistic tree pruning SD.     

An Efficient Parallel Architecture for Implementing LST Decoding in MIMO Systems

Recovering the symbols in a multiple-input multiple-output (MIMO) receiver is a computationally intensive process. The layered space–time (LST) algorithms provide a reasonable tradeoff between complexity and performance. Commercial digital signal processors (DSPs) have become a key component in many high-volume products such as cellular telephones. As an alternative to power-hungry DSPs, we propose to use a moderately parallel single-instruction stream, multiple-data stream (SIMD) coprocessor architecture, called DSP-RAM, to implement an LST MIMO receiver that offers high performance with relatively low power consumption. For a typical indoor wireless environment, a 100-MHz DSP-RAM can potentially provide more than ten times greater decoding throughput at the receiver of a     

A Statistical Pruning Strategy for Schnorr-Euchner Sphere Decoding

The high computational complexity of maximum likelihood (ML) decoding can impact many applications such as code division multiple access (CDMA) and multiple-input multiple-output (MIMO) systems. The sphere decoder (SD) as an efficient ML decoder has therefore received significant attention in the wireless research community. This letter presents a new statistical method to reduce the complexity of the Schnorr and Euchner sphere decoder (SESD). The method uses a set of bounds, which are computed using the conditional probability based on the minimum metric of the current solution. A lookup tabic for the bounds can be computed offline. The proposed method is effective for any number of antennas with complexity savings about 50% or more over the conventional SD approach.     

Area-Efficient Antenna-Scalable MIMO Detector for K-best Sphere Decoding

K-best sphere decoding is one of the most popular MIMO (Multi-Input Multi-Output) detection algorithms because of its low complexity and close to Maximum Likelihood (ML) Bit Error Rate (BER) performance. Unfortunately, conventional multi-stage sphere decoders suffer from the inability to adapt to varying antenna configurations, requiring implementation redesign for each specific array structure. In this paper, we propose a reconfigurable in-place architecture that is scalable to an arbitrary number of antennas at run-time, while reducing area significantly compared with other sphere decoders. To improve the throughput of the in-place architecture without any degradation in BER performance, we propose partial-sort-bypass and symbol interleaving techniques, and also exploit multi-core design. Implementation results for a 16-QAM MIMO decoder in a 130 nm CMOS technology show a 41% reduction in area compared to the smallest sphere decoder while maintaining antenna reconfigurability, and better throughput. When implemented for the 802.11n standard, our architecture results in 42% reduction in area compared to the multi-stage architecture.     

A Flexible DSP Architecture for MIMO Sphere Decoding

This paper presents the architecture and circuit design of a sphere decoder for agile multi-input multi-output (MIMO) communication systems. Algorithm and architecture co-design is used to reduce hardware complexity, which enables the proposed sphere decoder to support larger antenna-array sizes and higher order modulations. The proposed architecture is also capable of processing multiple frequency subcarriers for orthogonal frequency-division multiplexing (OFDM) based systems. A 20 times area reduction is achieved, even without interleaving of subcarriers compared to the direct-mapped architecture. The sphere decoder supports multiple configurations: antenna arrays from 2 times 2 to 16 times 16, constellation sizes from binary phase-shift keying (BPSK) to 64-QAM (quadrature-amplitude modulation), and 16-128 subcarriers. The peak estimated data rate exceeds 1.5 Gbits/s of ideal throughput in a 16-MHz bandwidth. The core area is estimated at 0.31 mm² in a standard 90-nm CMOS technology. The estimated power consumption is 33 mW in the 16 times 16 64-QAM mode at 256 MHz from a 1-V supply voltage.     

Blind Linear MMSE Receivers for MC-CDMA Systems

This paper studies blind constrained minimum output energy (CMOE)-based and subspace-based linear minimum mean-squared-error (LMMSE) detectors for multi-carrier code division multiple access (MC-CDMA) systems. By imposing quadratic weight constraint, the CMOE detector is made more robust against signature waveform mismatch, and a better performance over the standard CMOE detector is obtained. Because of separation of signal and noise subspaces, the more complicated subspace-based LMMSE detector has better performance than the CMOE detector. The recursive subspace tracking algorithms are also investigated for the subspace-based MMSE receiver. Numerical results show that the steady-state performance of the robust CMOE detector is close to the subspace-based MMSE method. The blind mode decision-directed LMMSE detection is studied where the blind detectors are used for initial adaptation. Numerical simulations illustrate that the blind mode decision-directed MMSE detection substantially improves the system performance when the frequency-selective channel is slowly-varying     

New SNR Adaptive Sphere Decoding Algorithm

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.     

相关信道MIMO系统的白适应SD检测算法

文章提出一种适用于相关衰落信道的自适应SD检测算法,该算法能够根据信道状况和接收信号信噪比自适应地进行调整。仿真结果表明,该算法能在不明显降低SD检测性能的情况下降低算法的计算复杂度。     

Transmission Strategies for MISO Downlink MC-CDMA Mobile Systems

This paper proposes two space-frequency schemes with a multi-user pre-filtering technique for downlink (DL) multicarrier code division multiple access (MC-CDMA) systems. We consider the use of antenna arrays at the base station (BS) and a single antenna at the mobile terminal (MT) and derive the proposed multi-user pre-filtering technique that modulates the transmitted signal to eliminate the effects of multiple access interference (MAI) and channel distortions at the mobile terminals, while maintaining low MT complexity. Two types of detectors are considered at the MT: simple despreading and single user equalizers. The performances of the proposed schemes are compared to those of other transmit signal design approaches that have been recently proposed for DL MC-CDMA, considering both typical indoor and pedestrian scenarios, and channel coding based on UMTS specifications.     

MC-CDMA系统中的帧同步

简要介绍了多载波码分多址(MC-CDMA)系统,重点讨论MC-CDMA的帧同步问题.在介绍循环前缀(CP)同步算法的基础上,对基于CP的最大似然估计(ML)的似然函数进行了改进,改进方案大大降低了系统的复杂度,仿真表明性能优异,具有较高的实用价值.