OFDM稀疏信道估计中导频设计算法

由于无线信道固有的稀疏性,压缩感知理论已被应用于正交频分复用(OFDM)系统的信道估计中来提高频谱利用率。文中研究OFDM系统稀疏信道中确定性导频的设计问题,针对互相关最小准则的不足,提出了一种基于测量矩阵互相关和测量矩阵列相关平方和最小化的联合算法。仿真结果表明,该算法的归一化均方误差(MSE)和误码率(SER)性能均优于基于互相关最小准则的随机搜索导频,相比于最小二乘算法,稀疏信道估计使用了更少的导频获得了更好的估计效果,提高了频谱利用率。     

基于混合遗传算法的导频优化

OFDM系统中,基于压缩感知的稀疏信道估计能够充分利用无线信道的固有稀疏性,进而降低导频开销,提高频谱利用率。针对压缩感知信道估计的导频设计,通过最小化压缩感知理论中测量矩阵的互相关性,提出一种基于混合遗传算法的导频优化方法。该方案首先采用遗传算法获得次优初始导频序列,然后结合导频位置以及导频功率对导频序列逐位进行替换、优化,以使测量矩阵的互相关性最小。MATLAB 仿真结果表明,相比于伪随机导频设计和等间距导频设计,该算法能够保证较低的均方误差和误码率。     

GNSS信号数据/导频扩频码配对优化方法

为了提高载波相位跟踪的稳健性和伪码跟踪精度,现代全球卫星导航系统(Global Navigation Satellite System,GNSS)普遍采用数据/导频并存的信号结构。针对数据/导频信号的互相关性影响码跟踪性能的问题,提出了一种数据/导频扩频码配对优化方法。优化准则是:在一定的超前减滞后间距条件下,单独跟踪导频信号时通道内互相关干扰导致的码跟踪平均误差最小。以全球定位系统(Global Positioning System,GPS)L1C频点信号为例,基于接口控制文件(Interface Control Document,ICD)给出的扩频码族,进行了数据/导频扩频码的配对优化设计,并仿真对比了不同配对方案的码跟踪性能。分析结果表明,优化后的配对方案能有效削弱数据/导频通道内的互相关干扰,提高导航信号的码跟踪性能。     

分布式空频编码协同通信系统中基于导频转发新时序的信道估计算法

该文针对频率选择性衰落下的多中继分布式空频编码协同通信系统,提出了基于导频转发新时序的频域信道估计算法,包括最小二乘(LS)估计算法和低阶近似的线性最小均方误差(Lr-LMMSE)估计算法。互相协同的各中继节点在收到源节点广播发送的频域导频符号向量后,通过互不相同的时隙将其转发给目的节点,从而避免了各中继节点转发的导频符号在目的节点上的混叠干扰。理论分析和仿真结果表明,该算法成功地分辨了多中继协同通信系统的所有频域信道系数,其估计精度高,算法复杂度低,具有较高的实用价值。     

MIMO-MC-CDMA系统中信道估计算法的比较

无线通信系统中最常用的就是使用导频来获得初始的信道响应,信道估计的目的就是通过导频序列来获得每个子信道上的信道状态信息(CSI).但是对于何种场合要运用何种导频方式并没有具体的文章描述清楚,文中给出了MIMO-MC-CDMA系统中常用的3种信道估计算法,分别是基于分散导频(梳状导频)、正交导频、分组导频(块状导频).通过分析这三种信道估计方法,得出结论.     

基于预编码与导频分配的大规模MIMO导频污染抑制

导频污染问题是限制大规模多输入多输出(MIMO)系统性能的主要影响因素.针对这个问题,提出了一种基于改进预编码和最优导频分配策略的大规模MIMO系统导频污染抑制算法.首先,在系统下通过基于改进遗传优化算法的最大化信干噪比(SINR)预编码算法,获得最优预编码矩阵;然后,通过基于用户信道条件优劣的最优导频分配策略对每个小区用户进行导频分配,从而实现大规模MIMO系统导频污染抑制.通过Matlab仿真结果可知,相对于传统的SINR预编码算法,所提算法的复杂度降低了65%左右,而导频污染抑制性能提升了30%左右.该算法能够有效抑制导频污染,提升大规模MIMO系统的性能.     

认知无线电NC-OFDM系统中基于压缩感知的信道估计新方法

提出了一种基于压缩感知(CS,compressive sensing)理论的不连续子载波正交频分复用(NC-OFDM,non-contiguous orthogonal frequency division multiplexing)系统信道估计新方法,全面研究了认知无线电NC-OFDM系统CS信道估计的理论框架、导频图案的设计、信道估计算法,并依据CS测量矩阵设计理论提出了测量矩阵互相关最小化的导频图案优化准则。仿真结果表明,同已有的NC-OFDM系统信道估计方法相比,CS信道估计能够在多种禁用子载波场景下,使用较少导频获得很好的信道估计性能。     

基于OFDM调制的可见光通信系统的导频设计

研究了基于正交频分复用(OFDM)调制的可见光通信(VLC)系统的导频设计方法.针对室内可见光通信信道特性,研究了导频数目对于信道容量的影响,从理论上给出了导频间隔与信道容量下界的关系式.在此基础上,建立了基于OFDM调制的可见光通信实验系统,并以上述理论关系式作为导频数目的设计依据.实验结果表明,随着导频间隔的变化,实验系统得到的系统频谱效率与理论给出的信道容量下界的变化趋势吻合,即文章提出的导频间隔与信道容量下界的理论关系式为可见光通信的最优导频间隔设计提供了理论依据.     

基于遗传算法的短波OFDM信道估计导频优化方案

短波信道具有时域稀疏性,压缩感知理论应用于短波OFDM信道估计可以改善估计性能以及减少导频开销。然而信道估计性能和信道的可恢复性都与导频的放置有着密切关系,为了进一步提高信道重构精度,本文以最小化测量矩阵的互相关为导频优化目标,提出一种基于遗传算法的导频优化方案,并设计了相应的交叉算子和变异算子,以产生新个体,保证种群的多样性。仿真结果表明,相比随机搜索,该方案可以得到更小的互相关值,更高的重构精度以及更高的频带利用率。     

基于梳状导频的OFDM信道估计算法研究

介绍了OFDM(正交频分复用)系统和基于导频的OFDM信道估计算法,主要对梳状导频插入的MMSE(最小均方误差)算法以及各种插值算法进行了研究,并对上述算法进行了仿真分析,最后在此基础上提出了进一步的研究方向。     

Pilot Optimization for Structured Compressive Sensing Based Channel Estimation in Large-Scale MIMO Systems with Superimposed Pilot Pattern

Compressive sensing (CS) has attracted much attention in wireless communications due to its ability to attain acceptable channel estimates with a small number of pilots. To further reduce the pilot overhead in multi-input multi-output (MIMO) systems, CS-based channel estimation may employ superimposed pilot pattern. Previous works on superimposed pilot design generally allocate pilots randomly, which may give ill-posed measurement matrices. In this paper, we focus on deterministic pilot allocation for large-scale MIMO systems with superimposed pilot pattern to improve the performance of structured CS based channel estimation. By exploiting the spatial common sparsity and the error bound of block sparse reconstruction, a new criterion is firstly proposed to optimize the pilots in the Hadamard space. The proposed criterion makes full use of the information about the principal angles across the blocks in the measurement matrix, which can enhance the average recovery ability and exclude the worst pilots simultaneously. Secondly, a genetic algorithm is proposed to minimize the merit factor of the proposed criterion efficiently. Simulation results show that the proposed optimized pilots outperform the random pilots in terms of mean-squared error by about 3 dB. Moreover, the proposed criterion is more likely to achieve better measurement matrices than the traditional criteria.     

OFDM稀疏信道估计中基于树状随机搜索导频设计新方法

压缩感知（CS,Compressed Sensing）是一种以低速率对稀疏信号进行采样后在接收端重建信号的技术,基于CS的稀疏信道估计具有更小的导频开销且具有更好的信道估计性能。针对基于CS的OFDM稀疏信道估计中的导频设计问题,提出一种基于树状随机搜索算法（TSS,Tree-based Stochastic Search Algorithm）的导频位置设计新方法,该方法结合了树的结构,以分支的方式进行随机搜索从而避免陷入局部最优问题。仿真结果表明,与传统的导频设计方法相比,使用TSS算法获得的导频图案用于信道估计中能够获得更优的信道估计性能,而且TSS算法的复杂度更低。      

Interference alignment scheme for massive MIMO system

The performance of massive multiple-input multiple-output （MIMO） system is limited by pilot contamination. To reduce the pilot contamination, uplink and downlink precoding algorithms are put forward based on interference alignment criterion. In the uplink receiving processing, the target function aligns the pilot contamination and the interference signals to the same null space and acquires the maximal space degree of the desired signals. The uplink receiving precoding matrix is solved on maximal signal to interference plus noise ratio （SINR） criterion considering the impact of the pilot contamination on channel estimations. The uplink receiving precoding matrix is used as the downlink transmitting precoding matrix. Exploiting the channel reciprocity, it is proved that, if the uplink receiving precoding matrix achieves maximal S1NR, the identical precoding matrix can be used in the downlink transmission and acquires maximal signal to leakage plus noise ratio （SLNR）. Simulations show that the spectrum efficiency of the proposed algorithm can reach about 1.5 times higher than that of popular matched filtering （MF） precoding algorithm, and about 1.1 times higher than multi-cell minimum mean square error （MMSE） precoding algorithm. The performance of the proposed algorithm can be improved approximately linearly with the increasing of the number of antennas.     

A low complexity DFT-matrix based pilot allocation algorithm for sparse channel estimation in OFDM systems

The accuracy of channel estimation is very important for Orthogonal Frequency Division Multiplexing (OFDM) systems. In a high speed wideband wireless communication, the channel can be modeled as a sparse one. Therefore, the Compressed Sensing (CS) technique can be used for the estimation of the channel. In this paper, the problem of deterministic pilot allocation in OFDM systems is considered and a new criterion which is based on minimizing the summation of the correlations between the columns of the Discrete Fourier Transform (DFT) sub-matrix is proposed. It will be shown that the proposed criterion is a simple version of the well-known but complex criterion, Restricted Isometry Property (RIP). In addition, the pilot pattern design, using our proposed scheme, indicates better recovery performance than other proposed coherence based criteria in terms of the reconstruction mean square error (MSE) and successful channel recovery percentage. Simulation results confirm our analysis.     

Iterative channel estimation and pilot design rules for high‐mobility comb‐pilot OFDM system

With wireless communications in high‐mobility environment becoming popular, this poses a big challenge for communication systems based on the comb‐pilot OFDM, such as IEEE 802.11p, since it has not the enough pilots to estimate the time‐ and frequency‐selective channel accurately. In this paper, several comb‐pilot schemes and three comb‐pilot design rules are proposed to meet the Nyquist criterion for sampling the vehicle‐to‐vehicle (V2V) channel and the requirements of second‐order statistic of V2V channel. Based on the proposed pilot schemes, an iterative channel estimation method from the CE‐BEM model is proposed, together with three ICI cancellation methods. After thorough simulation, the effectiveness of the comb‐pilot design rules, the proposed channel estimation method, and intercarrier interference (ICI) cancellation methods is verified. Compared with other channel estimation methods, the proposed method performs better. The simulation results also reveal that the channel order L+1 has a great impact on the performance of the comb‐pilot OFDM system.     

A Dynamic Optimal Pilot Design Method for OFDM Systems

Wireless communication systems are increasingly adopting orthogonal frequency division multiplexing to enable high data rate transmission. Such systems employ pilot symbols to estimate wireless channels. While pilot symbols facilitate channel acquisition, they consume part of bandwidth, which in turn reduces spectral efficiency. In this paper, a new pilot design method with virtual subcarriers is proposed. The pilots can be dynamic designed with the previous bit error rate (BER) and signal-to-noise ratio (SNR). The BER sectioned is utilized as the performance metric for the optimization of the total number of pilots. And then the proposed scheme maximizes a simple function relevant to SNR strategy based on the allocation of pilot locations. So the dynamic pilot design will optimize the total number and locations jointly and offer the potential of enhancing data rate while maintaining the quality of service in time-varying wireless channels. Comparing with the conventional pilot design which is commonly used in many protocols, the proposed scheme is more robust to the channel state, which could make good trade-off between data transmission efficiency and channel estimate accuracy.     

Hidden Pilot Based Precoder Design for MIMO-OFDM Systems

In order to improve bandwidth efficiency and bit error rate (BER) performance, a new hidden pilot scheme using a precoder is proposed for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. We show that the inevitable data interference of the hidden pilot, which degrades the performance of channel estimation, can be reduced successfully by the precoder design for each antenna with the aid of an iterative scheme. We also show that frequency diversity gain can be achieved due to the spreading effect of the precoder. Computer simulations are presented in which the proposed scheme is compared with conventional methods with respect to channel estimation, BER and bandwidth efficiency.