Blind Receiver Design for OFDM Systems Over Doubly Selective Channels

We develop blind data detectors for orthogonal frequency-division multiplexing (OFDM) systems over doubly selective channels by exploiting both frequency-domain and time-domain correlations of the received signal. We thus derive two blind data detectors: a time-domain data detector and a frequency-domain data detector. We also contribute a reduced complexity, suboptimal version of a time-domain data detector that performs robustly when the normalized Doppler rate is less than 3%. Our frequency-domain data detector and suboptimal time-domain data detector both result in integer least-squares (LS) problems. We propose the use of the V-BLAST detector and the sphere decoder. The time-domain data detector is not limited to the Doppler rates less than 3%, but cannot be posed as an integer LS problem. Our solution is to develop an iterative algorithm that starts from the suboptimal time-domain data detector output. We also propose channel estimation and prediction algorithms using a polynomial expansion model, and these estimators work with data detectors (decision-directed mode) to reduce the complexity. The estimators for the channel statistics and the noise variance are derived using the likelihood function for the data. Our blind data detectors are fairly robust against the parameter mismatch     

一种实用的基于导频的空时编码OFDM系统信道估计方法

该文研究了在多径衰落信道情况下的基于导频的空时编码OFDM系统的信道估计方法,包括基于DFT的LS,LMMSE算法,提出了一种实用的估计方法,该方法通过优化设计的导频符号避免了复杂的矩阵求逆计算,大大降低了LS,LMMSE算法的复杂度和运算量,在性能上接近理想信道信息情况下的性能。     

应用符号相关性的认知OFDM系统信噪比盲估计

针对认知无线电系统中OFDM(orthogonal frequency division multiplexing)信号信噪比估计算法适用范围受限、复杂度高的问题,提出一种新的基于符号相关性的信噪比盲估计算法,算法首先通过扩展前缀相关性检测区间得到一个特征序列,然后通过小波消噪去除多径信道的影响,最后通过序列极大值极小值与信号功率及噪声方差的关系得到信噪比的估计值。仿真结果表明,本文算法能够实现对ZP-OFDM(zero-padding OFDM)信号信噪比的准确估计,同时在应用于CP-OFDM(cyclic-prefix OFDM)信噪比估计时适用范围更广、运算更为简便,更加适用于认知无线电系统。      

Precoded and vector OFDM robust to channel spectral nulls and withreduced cyclic prefix length in single transmit antenna systems

The performance of orthogonal frequency-division multiplexing (OFDM) systems may be degraded when intersymbol interference (ISI) channels have spectral nulls. Also, when ISI channels have many taps, the data rate overhead due to the insertion of the cyclic prefix is high. We first propose a precoded OFDM system that may improve the performance of the OFDM systems for spectral null channels. We also propose size K×x1 vector OFDM (VOFDM) systems that reduce the cyclic prefix length by K times compared to the conventional OFDM systems. The precoding scheme is simply to insert one or more zeros between each two sets of K consecutive information symbols, although it can be generalized to a general form. This precoding scheme may be able to remove the spectral nulls of an ISI channel without knowing the ISI channel. When no zero is inserted between each two sets of K consecutive information symbols and only each K consecutive symbols are blocked together, we obtain VOFDM systems. Both theoretical performance analysis and simulation results are presented. Finally, we compare the combination of the VOFDM systems and the unitary matrix modulation with the conventional OFDM systems and the phase-shift keying modulation, where both differential (noncoherent) and coherent modulations and demodulations are considered     

一种基于空时相关的MIMO OFDM系统信道估计算法

提出了一种基于空时相关的MIMO OFDM系统信道估计算法,该算法以时域最小二乘信道估计(TD-LS-CE)为初始估计,充分利用在接收端已知的空时相关性,通过最小化FIR窗内多符号平均意义上的信道估计均方误差(MSE),获得对初始信道估计进行空时滤波的最优权系数,并进一步利用奇异值分解的方法大大降低该信道估计算法的复杂度。最后仿真结果表明,在相同的条件下,该信道估计算法在MSE、BER方面优于传统滑动平均(MA)信道估计算法在其最佳窗长时的性能,且在一定条件下可逼近理想信道估计性能。此外,空时相关性的增强还可进一步改善该信道估计算法的性能。     

Joint Semi-Blind Channel Estimation and Data Sequence Detection of OFDM Systems

1　ＩｎｔｒｏｄｕｃｔｉｏｎＴｈｅｅｘｐｌｏｓｉｖｅｇｒｏｗｔｈｏｆｗｉｒｅｌｅｓｓｃｏｍｍｕｎｉｃａ ｔｉｏｎｓｉｓｉｎｃｒｅａｓｉｎｇｔｈｅｄｅｍａｎｄｓｆｏｒｈｉｇｈ ｓｐｅｅｄ ,ｒｅｌｉ ａｂｌｅ,ａｎｄｓｐｅｃｔｒａｌｌｙｅｆｆｉｃｉｅｎｔｃｏｍｍｕｎｉｃａｔｉｏｎｓｏｖｅｒｗｉｒｅｌｅｓｓｍｅｄｉｕｍ[1～2 ] .Ｈｏｗｅｖｅｒ,ｔｈｅｒｅａｒｅｓｅｖｅｒａｌｃｈａｌｌｅｎｇｅｓｉｎａｔｔｅｍｐｔｓｔｏｐｒｏｖｉｄｅｈｉｇｈ ｑｕａｌｉｔｙｓｅｒｖｉｃｅｉｎｔｈｉｓｄｙｎａｍｉｃｅｎｖｉｒｏｎｍ…     

Polynomial Estimation of Time-Varying Multipath Gains With Intercarrier Interference Mitigation in OFDM Systems

In this paper, we consider the case of a high-speed mobile receiver operating in an orthogonal frequency-division multiplexing (OFDM) communication system. We present an iterative algorithm for estimating multipath complex gains with intersubcarrier interference (ICI) mitigation (using comb-type pilots). Each complex gain variation is approximated by a polynomial representation within several OFDM symbols. Assuming knowledge of delay-related information, polynomial coefficients are obtained from time-averaged gain values, which are estimated using the least-square (LS) criterion. The channel matrix is easily computed, and the ICI is reduced by using successive interference suppression (SIS) during data symbol detection. The algorithm's performance is further enhanced by an iterative procedure, performing channel estimation and ICI mitigation at each iteration. Theoretical analysis and simulation results for a Rayleigh fading channel show that the proposed algorithm has low computational complexity and good performance in the presence of high normalized Doppler spread.     

Low-Complexity Map Channel Estimation for Mobile MIMO-OFDM Systems

This paper presents a reduced-complexity maximum a posteriori probability (MAP) channel estimator with iterative data detection for orthogonal frequency division multiplexing (OFDM) systems over mobile multiple-input multiple- output channels. The optimal MAP estimator needs to invert an NN_T x NN_T data-dependent matrix each in OFDM symbol interval, where N is the number of subcarriers and N_T is the number of transmit antennas. We derive an expectation maximization (EM) algorithm with low-rank approximation to avoid inverting large-size matrices, and thus drastically reduce the receiver complexity. In the iterative process, channel parameters are initially obtained by a least square (LS) estimator for temporary symbol decisions. Then, inter-carrier interference (ICI) due to fast fading is approximated and canceled. Finally, the temporary symbol decisions and the ICI-canceled received signals are processed by the EM-based MAP estimator to refine the channel state information for improved detection. The proposed scheme achieves about 2 dB gain over the LS scheme in channels with medium to high normalized Doppler shifts.     

基于半定松弛方法的时变OFDM系统盲信道估计

该文提出了一种时变正交频分复用(OFDM)系统信道盲估计算法。在二次规范( Quadratic Program, QP)模型的基础上,采用半定松弛技术,把OFDM信道盲估计转换为一个可以在多项式时间内求解的半定规划问题。为了进一步降低半定规划问题的转换复杂度,考虑到OFDM各个子载波和各个时刻的响应之间的紧相关性,该文提出了一种新的随机转换策略,仿真表明,该文所提出的算法,其误码率逼近最佳估计,且复杂度大幅降低。     

Structure-Based Low Complexity MMSE Channel Estimator for OFDM Wireless Systems

Wireless communication systems utilizing orthogonal frequency division multiplexing (OFDM) transmissions are capable of delivering high data rates over multipath frequency selective channels. This paper deals with joint estimation/interpolation of wireless channel using pilot symbols transmitted concurrently with the data. We propose a low complexity, spectrally efficient minimum mean square error channel estimator which exploits the correlation structure of channel frequency response for reducing the complexity. Specifically, it is shown that if pilots are inserted appropriately across OFDM subcarriers, the proposed algorithm requires no matrix inversion, thereby significantly relieving the computational burden without deteriorating the performance. Moreover, the knowledge of channel correlation is also not required for the proposed estimator. Simulation results validate that the proposed technique outperforms existing low-complexity variants in terms of mean square error and computational complexity.

     

Totally blind APP channel estimation for mobile OFDM systems

A new two-dimensional blind channel estimation scheme for coherent detection of orthogonal frequency-division multiplexing (OFDM) signals in a mobile environment is presented. The channel estimation is based on the a posteriori probability (APP) calculation algorithm. The time-variant channel transfer function is completely recovered without phase ambiguity with no need for any pilot or reference symbols, thus maximizing the spectral efficiency of the underlying OFDM system. The phase ambiguity problem is solved by using a 4-QAM (quadrature amplitude modulation) scheme with asymmetrical arrangement. The results clearly indicate that totally blind channel estimation is possible for virtually any realistic time-variant mobile channel.     

A sequential Monte Carlo blind receiver for OFDM systems infrequency-selective fading channels

We consider the application of the sequential Monte Carlo (SMC) methodology to the problem of blind symbol detection in a wireless orthogonal frequency-division multiplexing (OFDM) system over a frequency-selective fading channel. Bayesian inference of the unknown data symbols in the presence of an unknown multipath fading channel is made only from the observations over one OFDM symbol duration. A novel blind SMC detector built on the techniques of importance sampling and resampling is developed for differentially encoded OFDM systems. The performance of different schemes of delayed-weight estimation methods is studied. Furthermore, being soft-input and soft-output in nature, the proposed SMC detector is employed as the first-stage demodulator in a turbo receiver for a coded OFDM system. Such a turbo receiver successively improves the receiver performance by iteratively exchanging the so-called extrinsic information with the maximum a posteriori (MAP) outer channel decoder. Finally, the performance of the proposed sequential Monte Carlo receiver is demonstrated through computer simulations     

OFDM channel estimation with dispersive fading channels

In this paper, we studied the channel estimation problem for the orthogonal frequency division multiplexing (OFDM) system when the statistics of the multi-path fading channel is not known or partial known. A channel estimation approach based on polynomial approximation of the channel response is proposed. The pilot symbols are periodically inserted the channel responses for entire OFDM data sequence for exploiting channel correlation in both time and frequency domain, which is obtained from a time-variant frequency-selective Rayleigh fading channel model. Simulation shows that the method is robust to different channel statistics. Moreover, a window dimension adaptation algorithm is proposed to adapt the channel estimator to the channel statistics which further improves the robustness of the system.     

基于电力线信道的OFDM盲同步算法

在Takahashi提出的盲同步算法的基础上,提出了一种OFDM多符号联合的差分盲同步算法。同Takahashi的算法一样,该算法利用OFDM符号的循环前缀内不被多径时延扩展所影响的那部分码元提取定时信息,但是为了避免电力线信道中随机的脉冲噪声对符号同步产生的影响,在每个定时时刻,取差值的前后移动平均,并采用多个OFDM符号的联合,以增强同步效果。仿真结果表明,在第一径为最强径或是非最强径的电力线多径衰落信道中,该算法取得了很好的符号同步效果。     

A Flexible Peak-To-Average Power Ratio Reduction Scheme for OFDM Systems by the Adaptive Projected Subgradient Method

One of the main issues of the orthogonal frequency-division multiplexing (OFDM) modulation is the high peak-to-average power ratio (PAPR) of the transmitted signal, which adversely affects the complexity of power amplifiers. In this paper, we consider transmitters that reduce the PAPR by slightly disturbing the symbols in carriers used to transmit information and by sending dummy symbols—i.e., symbols not conveying information—in unused carriers. The optimal choice of the data and dummy symbols is determined by the solution of a convex optimization problem. To reduce the PAPR with low complexity, we apply a modified version of the adaptive projected subgradient method to a sequence of convex cost functions closely related to the original optimization problem. The resulting algorithm achieves near-optimal PAPR in practical scenarios, generalizes existing algorithms based on Polyak's method, and can easily handle multiple constraints.      

Near-optimum soft decision equalization for frequency selective MIMO channels

In this paper, we develop soft decision equalization (SDE) techniques for frequency selective multiple-input multiple-output (MIMO) channels in the quest for low-complexity equalizers with error performance competitive to that of maximum likelihood (ML) sequence detection. We demonstrate that decision feedback equalization (DFE) based on soft-decisions, expressed via the posterior probabilities associated with feedback symbols, is able to outperform hard-decision DFE, with a low computational cost that is polynomial in the number of symbols to be recovered and linear in the signal constellation size. Building on the probabilistic data association (PDA) multiuser detector, we present two new MIMO equalization solutions to handle the distinctive channel memory. The first SDE algorithm adopts a zero-padded transmission structure to convert the challenging sequence detection problem into a block-by-block least-square formulation. It introduces key enhancement to the original PDA to enable applications in rank-deficient channels and for higher level modulations. The second SDE algorithm takes advantage of the Toeplitz channel matrix structure embodied in an equalization problem. It processes the data samples through a series of overlapping sliding windows to reduce complexity and, at the same time, performs implicit noise tracking to maintain near-optimum performance. With their low complexity, simple implementations, and impressive near-optimum performance offered by iterative soft-decision processing, the proposed SDE methods are attractive candidates to deliver efficient reception solutions to practical high-capacity MIMO systems. Simulation comparisons of our SDE methods with minimum-mean-square error (MMSE)-based MIMO DFE and sphere decoded quasi-ML detection are presented.     

Peak power reduction for OFDM systems with orthogonal pilot sequences

In this paper, a novel peak-to-average power reduction approach for orthogonal frequency division multiplexing (OFDM) has been addressed. Two-dimensional pilot-symbol assisted modulation (2D-PSAM) is employed in coherent OFDM for channel estimation, and it is based on inserting known symbols spread throughout the 2D time-frequency grid. These pilot symbols are employed to simultaneously perform distortionless peak power reduction with a suboptimum technique named orthogonal pilot sequences (OPS), which reduces additional system complexity and side information compared to optimum pilot values. This proposal attains a further step over other previous works, since this set of sequences allows blind detection at the receiver without prior knowledge of any side information.     

A reduced complexity channel estimation for OFDM systems withtransmit diversity in mobile wireless channels

A reduced complexity channel estimation for OFDM systems with transmit diversity is proposed by exploiting the correlation of the adjacent subchannel responses. The sizes of the matrix inverse and the FFTs required in the channel estimation at every OFDM data symbol are reduced by half of the existing method for OFDM systems with nonconstant modulus subcarrier symbols or constant modulus subcarrier symbols with some guard tones. The complexity reduction of half FFTs size and some matrix multiplications is still achieved for constant modulus subcarrier symbols with no guard tones. The price for the complexity reduction is a slight BER degradation and for the channels with small relative delay spreads, the BER performance of the reduced complexity method becomes quite comparable to the existing method. An alternative approach for the number of significant taps required in the channel estimation is described which achieves a comparable performance to the case with the known suitable number of significant taps. A simple modification which reduces the lost leakage of the nonsample-spaced channel paths is also proposed. This modification achieves a substantial performance improvement over the existing method without any added complexity     

Blind adaptive channel estimation in ofdm systems

We consider the problem of blind channel estimation in zero padding OFDM systems, and propose blind adaptive algorithms in order to identify the impulse response of the multipath channel. In particular, we develop RLS and LMS schemes that exhibit rapid convergence combined with low computational complexity and numerical stability. Both versions are obtained by properly modifying the orthogonal iteration method used in numerical analysis for the computation of singular vectors. With a number of simulation experiments we demonstrate the satisfactory performance of our adaptive schemes under diverse signaling conditions     

Low complexity channel estimation for space-time coded wideband OFDM systems

In this article, channel estimation for space-time coded orthogonal-frequency division multiplexing (OFDM) systems is considered. By assuming that the channel frequency response is quasi-static over two consecutive OFDM symbols, we develop channel parameter estimators based on the use of space-time block coded (STBC) training blocks. Using an STBC training pattern, a low-rank Wiener filter-based channel estimator with a significant complexity reduction is proposed. A simplified approach for the optimal low-rank estimator is also proposed to further reduce the estimator complexity while retaining an accurate frequency domain channel estimation. Numerical results are provided to demonstrate the performance of the proposed low complexity channel estimators for space-time trellis coded OFDM systems.