Joint data detection and channel estimation for OFDM systems

We develop new blind and semi-blind data detectors and channel estimators for orthogonal frequency-division multiplexing (OFDM) systems. Our data detectors require minimizing a complex, integer quadratic form in the data vector. The semi-blind detector uses both channel correlation and noise variance. The quadratic for the blind detector suffers from rank deficiency; for this, we give a low-complexity solution. Avoiding a computationally prohibitive exhaustive search, we solve our data detectors using sphere decoding (SD) and V-BLAST and provide simple adaptations of the SD algorithm. We consider how the blind detector performs under mismatch, generalize the basic data detectors to nonunitary constellations, and extend them to systems with pilots and virtual carriers. Simulations show that our data detectors perform well.     

Blind and semiblind detections of OFDM signals in fading channels

This paper considers the problem of blind joint channel estimation and data detection for orthogonal frequency-division multiplexing (OFDM) systems in a fading environment. Employing a regression model for a time-varying channel, we convert the problem into one that finds the data sequence x whose associated least-squares (LS) channel estimate z(x) is closest to the space of some regression curves (surfaces). We apply the branch-and-bound principle to solve the nonlinear integer programming problem associated with finding the curve that fits a subchannel in the LS sense. A recursive formula for fast metric update is obtained by exploiting the intrinsic characteristic of our objective function. The impacts of reordering the data sequence and selective detection are addressed. By employing a preferred order along with a selective detection method, we greatly reduce the detector complexity while giving up little performance loss. Both the complete and the reduced-complexity algorithms can be used for blind and semiblind detections of OFDM signals in a subchannel-by-subchannel manner. To further reduce the complexity and exploit the frequency-domain channel correlation, we suggest a two-stage approach that detects a few selected positions in some subchannels first, and then, treating the detected symbols as pilots, determines the remaining symbols within a properly chosen time-frequency block by a two-dimensional model-based pilot-assisted algorithm. The proposed methods do not require the information of the channel statistics like signal-to-noise ratio or channel correlation function. Performance of differential modulations like differential quaternary phase-shift keying and STAR 16-ary quadrature amplitude modulation are provided. Both blind and semiblind schemes yield satisfactory performance.     

Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems

In time division-synchronous code division multiple access systems, the channel estimation for multiple subscribers requires the computation of very complicated algorithms through short training sequences. This situation causes mismodeling of the actual channels and introduces significant errors in the detected data of multiple users. This paper presents a novel channel estimation method with low complexity, which relies on reducing the rank order of the total channel matrix H. We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. Simulation results of the normalized mean square error for the above mentioned estimators showed the superiority of reduced rank estimators. Multi-user joint data detectors based linear equalizers are used to suppress inter-symbol interference and mitigate intra-cell multiple access interference. The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. The results of bit error rate simulation have shown that reduced rank-JCE based detectors have an improvement by 5 dB lower than other traditional full rank-JCE based detectors.     

Two novel iterative joint frequency-offset and channel estimation methods for OFDMA uplink

We address joint estimation of frequency offsets and channel responses in OFDMA uplink. A cyclically equal-spaced, equal-energy interleaved pilot preamble is proposed by which two iterative estimators are developed. In the first estimator, we develop a modified SAGE (space alternating generalized expectation-maximization) method by incorporating multiuser interference cancellation in both time and frequency domains into the SAGE method. The proposed modified SAGE method yields a faster convergence rate, a better estimation performance, and a lower complexity than the existing conventional SAGE method from [10]. In the second method, we propose a very low complexity ad hoc method to replace the high complexity frequency offset estimator of the first method. The proposed ad hoc method is developed based on the time-domain characteristics of the pilot preamble and the frequency-domain power concentration property of OFDMA systems. It achieves almost the same estimation performance as the first proposed method but requires significantly lower complexity. Both proposed methods are not only better in estimation performance, convergence rate, and complexity, but also more robust to the number of active uplink users than the existing method while requiring only one OFDM training symbol and no restriction of the data subcarrier assignment scheme.     

Interference estimation with applications to blind multiple-accesscommunication over fading channels

We consider the detection of nonorthogonal multipulse signals on multiple-access fading channels. The generalized maximum-likelihood rule is employed to decode users whose complex fading gains are unknown. We develop geometrical interpretations for the resulting detectors and their corresponding asymptotic efficiencies. The generalized maximum-likelihood detection rule is then applied to find a matched subspace detector for the frequency-selective fading channel, under the assumption of a short coherence time (or long coherence time without the computational power to track the fading parameters). We propose blind implementations of these detectors for nonorthogonal multipulse signaling on both frequency-nonselective and frequency-selective multiple-access fading channels. These blind detectors extend the results of Wang and Poor (see ibid., vol.44, p.677-89, 1998) to multipulse modulation and fast frequency selective fading. For comparison, the minimum mean-squared error decision rules for these channels are derived and blind implementations of their corresponding detectors are developed     

Nonlinear techniques for the joint estimation of cochannel signals

Cochannel interference occurs when two or more signals overlap in frequency and are present concurrently. Unlike in spread-spectrum multiple-access systems where the different users necessarily share the same channel, cochannel interference is a severe hindrance to frequency- and time-division multiple-access communications, and is typically minimized by interference rejection/suppression techniques. Rather than using interference suppression, we are interested in the joint estimation of the information-bearing narrow-band cochannel signals. Novel joint estimators are proposed that employ a single-input demodulator with oversampling to compensate for timing uncertainties. Assuming finite impulse-response channel characteristics, maximum likelihood (ML) and maximum a posteriori (MAP) criteria are used to derive cochannel detectors of varying complexities and degrees of performance. In particular, a (suboptimal) two-stage joint MAP symbol detector (JMAPSD) is introduced that has a lower complexity than the single-stage estimators while accruing only a marginal loss in error-rate performance at high signal-to-interference ratios. Assuming only reliable estimates of the primary and secondary signal powers, a blind adaptive JMAPSD algorithm for a priori unknown channels is also derived. The performance of these nonlinear joint estimation algorithms is studied through example computer simulations for two cochannel sources     

Receiver design for multicarrier CDMA using frequency-domain oversampling

Based on the frequency-domain oversampling and minimum mean-square error (MMSE) principles, we propose three linear single-user detectors for downlink multicarrier codedivision multiple-access (MC-CDMA) systems. We begin with an optimal linear MMSE detector, which is computationally demanding. To reduce the complexity, a two-stage MMSE detector and a diagonal one-stage MMSE detector are developed subsequently. Simulation results show that the proposed detectors can efficiently suppress the multiple access interference (MAI) caused by frequency-selective fading, near-far effect, frequency offset, and nonlinear power amplification.     

New-User Detection in Time Hopping Multi-User Environment for UWB Impulse Radio Systems

This paper addresses the problem of detecting a new user in time-hopping multiple access communication environment targeted for ultra wideband impulse radio (IR) systems. The proposed detector is based on exploiting the orthogonality between the new user and the other active user(s) in frequency domain. This is because the time-domain orthogonality is destroyed due to the long delay spread of a dense multipath channel experienced by IR transmission. This results in the presence of inter-frame, inter-path as well as inter-symbol interferences. To ensure the frequency-domain orthogonality, we propose a TH code design as a means of encoding a unique spectrum that is orthogonal to each user. Simulation results highlight the note-worthy improvement in frequency-domain detection performance that utilizes our proposed design algorithm. This gain is obtained without any significant increase in computational complexity or hardware costs. Unlike the rake detector, the frequency-domain detector does not require the time-of-arrival information of the multipath components.     

Adaptive joint multiuser detection and channel estimation in multipath fading CDMA channels

The problem of joint multiuser detection and channel estimation in frequency-selective Rayleigh fading CDMA channels is considered. First the optimal multiuser detector for such channels is derived, which is seen to have a computational complexity exponential in the product of the number of users and the length of the transmitted data sequence. Two suboptimal detectors are then developed and analyzed, both of which employ decorrelating filters at the front-ends to eliminate the multiple-access interference and the multipath interference. The symbol-by-symbol detector uses a Kalman filter and decision feedback to track the fading channel for diversity combining. The per-survivor sequence detector is in the form of the Viterbi algorithm with the trellis updates being computed by a bank of Kalman filters in the per-survivor fashion. Both suboptimal detectors require the knowledge of all waveforms of all users in the channel and the channel fading model parameters. Adaptive versions of these suboptimal detectors that require only the knowledge of the waveform of the user of interest are then developed. The adaptive receivers employ recursive-least-squares (RLS) minimum-mean-square-error (MMSE) filters at the front-end to mitigate the interference, and use a bank of linear predictors to track the fading channels. It is shown that the front-end RLS-MMSE filters can be implemented using systolic arrays to exploit massively parallel signal processing computation, and to achieve energy efficiency. Finally, the performance of the suboptimal detectors and their adaptive versions are assessed by simulations. This revised version was published online in July 2006 with corrections to the Cover Date.     

Bayesian decision feedback techniques for deconvolution

There has been great interest in reduced complexity suboptimal MAP symbol-by-symbol estimation for digital communications. We propose a new suboptimal estimator suitable for both known and unknown channels. In the known channel case, the MAP estimator is simplified using a form of conditional decision feedback, resulting in a family of Bayesian conditional decision feedback estimators (BCDFEs); in the unknown channel case, recursive channel estimation is combined with the BCDFE. The BCDFEs are indexed by two parameters: a “chip” length and an estimation lag. These algorithms can be used with estimation lags greater than the equivalent channel length and have a complexity exponential in the chip length but only linear in the estimation lags. The BCDFEs are derived from simple assumptions in a model-based setting that takes into account discrete signalling and channel noise. Extensive simulations characterize the performance of the BCDFE and BCDPE for uncoded linear modulations over both known and unknown (nonminimum phase) channels with severe ISI. The results clearly demonstrate the significant advantages of the proposed BCDFE over the BCDFE in achieving a desirable performance/complexity tradeoff. Also, a simple adaptive complexity reduction scheme can be combined with the BCDFE resulting in further substantial reductions in complexity, especially for large constellations. Using this scheme, we demonstrate the feasibility of blind 16QAM demodulation with 10^-4 bit error probability at E _b/N₀≈ 18.5 dB on a channel with a deep spectral null     

Optimal low-complexity detection for space division multiple access wireless systems

A symbol detector for wireless systems using space division multiple access (SDMA) and orthogonal frequency division multiplexing (OFDM) is derived. The detector uses a sphere decoder (SD) and has much less computational complexity than the naive maximum likelihood (ML) detector. We also show how to detect non-constant modulus signals with constrained least squares (CLS) receiver, which is designed for constant modulus (unitary) signals. The new detector outperforms existing suboptimal detectors for both uncoded and coded systems.     

Soft quasi-maximum-likelihood detection for multiple-antenna wireless channels

The paper addresses soft maximum-likelihood (ML) detection for multiple-antenna wireless communication channels. We propose a soft quasi-ML detector that maximizes the log-likelihood function by deploying a semi-definite relaxation (SDR). Given perfect channel state information at the receiver, the quasi-ML SDR detector closely approximates the performance of the optimal ML detector in both coded and uncoded multiple-input, multiple-output (MIMO) channels with quadrature phase-shift keying (QPSK) modulation and frequency-flat Rayleigh fading. The complexity of the quasi-ML SDR detector is much less than that of the optimal ML detector, thus offering more favorable performance/complexity characteristics. In contrast to the existing sphere decoder, the new quasi-ML detector enjoys guaranteed polynomial worst-case complexity. The two detectors exhibit quite comparable performance in a variety of ergodic QPSK MIMO channels, but the complexity of the quasi-ML detector scales better with increasing number of transmit and receive antennas, especially in the region of low signal-to-noise ratio (SNR).     

Linear space-time multiuser detection for multipath CDMA channels

We consider the problem of detecting synchronous code division multiple access (CDMA) signals in multipath channels that result in multiple access interference (MAI). It is well known that such challenging conditions may create severe near-far situations in which the standard techniques of combined power control and temporal single-user RAKE receivers provide poor performance. To address the shortcomings of the RAKE receiver, multiple antenna receivers combining space-time processing with multiuser detection have been proposed in the literature. Specifically, a space-time detector based on minimizing the mean-squared output between the data stream and the linear combiner output has shown great potential in achieving good near-far performance with much less complexity than the optimum space-time multiuser detector. Moreover, this space-time minimum mean-squared error (ST-MMSE) multiuser detector has the additional advantage of being well suited for adaptive implementation. We propose novel trained and blind adaptive algorithms based on stochastic gradient techniques, which are shown to approximate the ST-MMSE solution without requiring knowledge of the channel. We show that these linear space-time detectors can potentially provide significant capacity enhancements (up to one order of magnitude) over the conventional temporal single-user RAKE receiver     

Analysis of Differential Orthogonal Space–Time Block Codes Over Semi-Identical MIMO Fading Channels

We study the performance of differential orthogonal space-time block codes (OSTBC) over independent and semi-identically distributed block Rayleigh fading channels. In this semiidentical fading model, the channel gains from different transmit antennas to a common receive antenna are identically distributed, but the gains associated with different receive antennas are nonidentically distributed. Arbitrary fluctuation rates of the fading processes from one transmission block to another are considered. We first derive the optimal symbol-by-symbol differential detector, and show that the conventional differential detector is suboptimal. We then derive expressions of exact bit-error probabilities (BEPs) for both the optimal and suboptimal detectors. The results are applicable for any number of receive antennas, and any number of transmit antennas for which OSTBCs exist. For two transmit antennas, explicit and closed-form BEP expressions are obtained. For an arbitrary number of transmit antennas, a Chernoff bound on the BEP for the optimal detector is also derived. Our results show that the semi-identical channel statistics degrade the error performance of differential OSTBC, compared with the identical case. Also, the proposed optimal detector substantially outperforms the conventional detector when the channel fluctuates rapidly. But in near-static fading channels, the two detectors have similar performances     

Blind turbo multiuser detection for long-code multipath CDMA

We consider the problem of demodulating and decoding multiuser information symbols in an uplink asynchronous coded code-division multiple-access (CDMA) system employing long (aperiodic) spreading sequences, in the presence of unknown multipath channels, out-cell multiple-access interference (OMAI), and narrow-band interference (NBI). A blind turbo multiuser receiver, consisting of a novel blind Bayesian multiuser detector and a bank of MAP decoders, is developed for such a system. The effect of OMAI and NBI is modeled as colored Gaussian noise with some unknown covariance matrix. The main contribution of this paper is to develop blind Bayesian multiuser detectors for long-code multipath CDMA systems under both white and colored Gaussian noise. Such detectors are based on the Bayesian inference of all unknown quantities. The Gibbs sampler, a Markov chain Monte Carlo procedure, is then used to calculate the Bayesian estimates of the unknowns. The blind Bayesian multiuser detector computes the a posteriori probabilities of the channel coded symbols, which are differentially encoded before being sent to the channel. Being soft-input soft-output in nature, the proposed blind Bayesian multiuser detectors and the MAP decoders can iteratively exchange the extrinsic information to successively refine the performance, leading to the so-called blind turbo multiuser receiver     

16DAPSK+OFDM及其在数字调幅广播中应用

本文提出一种新的频域16DAPSK＋OFDM。并讨论它的频域差分调制和解调,然后在白高斯信道分析它的误比特性能。同时域16DASK＋OFDM相比,频域16DAPSK＋OFDM可用于信道特性随时间变化更快的应用。最后,在典型的调幅（AM）波段信道对两者误比特性能进行了仿真。结果表明,时域和频域16DPSK＋OFDM都可用于中短波信道。在中波信道,时域16DAPSK比例域16DAPSK性能要好,在短波信道,频域16DAPSK比时域16DAPSK性能要好。另外,两者调制和解调的计算复杂度基本一样,且都不需要信息道均衡。     

MB-OFDM-UWB系统基于时域扩展的盲频率跟踪算法

对多频带正交频分复用超宽带系统同步技术进行研究,提出一种基于时域扩展技术（TDS）的盲载波频偏（CFO）跟踪算法。利用数据符号与其时域扩展符号的特殊映射关系,在时域和频域分别推导出残余载波频偏的盲估计公式,并构建相应的时频跟踪环路。仿真结果表明,该盲算法具有比导频辅助法更优的跟踪性能。10dB信噪比下,基于TDS进行时频跟踪的残余CFO均方根误差均达到2×10?4,系统误比特率可达10?6数量级。     

Equalization for OFDM over doubly selective channels

In this paper, we propose a time-domain as well as a frequency-domain per-tone equalization for orthogonal frequency-division multiplexing (OFDM) over doubly selective channels. We consider the most general case, where the channel delay spread is larger than the cyclic prefix (CP), which results in interblock interference (IBI). IBI in conjunction with the Doppler effect destroys the orthogonality between subcarriers and, hence, results in severe intercarrier interference (ICI). In this paper, we propose a time-varying finite-impulse-response (TV-FIR) time-domain equalizer (TEQ) to restore the orthogonality between subcarriers, and hence to eliminate ICI/IBI. Due to the fact that the TEQ optimizes the performance over all subcarriers in a joint fashion, it has a poor performance. An optimal frequency-domain per-tone equalizer (PTEQ) is then obtained by transferring the TEQ operation to the frequency domain. Through computer simulations, we demonstrate the performance of the proposed equalization techniques.     

Near optimum tree-search detection schemes for bit-synchronousmultiuser CDMA systems over Gaussian and two-path Rayleigh-fadingchannels

Simple reduced tree-search detection schemes of the breadth-first type are applied to suboptimal joint multiuser detection in bit-synchronous code-division multiple access (CDMA) systems over both Gaussian and two-path Rayleigh-fading channels. It is pointed out that in contrast to the case of the optimal multiuser detector, the choice of the receiver filter severely influences the performance of suboptimal multiuser detectors. Simulation results supported by analysis show that breadth-first tree-search algorithms using a decorrelating noise whitening receiver filter perform better than similar receivers, which solely use a matched filter (MF) for virtually all nonsingular spreading code sets studied. Most of the code sets are randomly generated. The M- and T-algorithm detectors based on decorrelating noise whitening filter (WF) outputs can achieve near optimum performance at a very low complexity compared to the optimal detector, although the proposed detectors are more complex than some known suboptimum detectors. Furthermore, the use of combining techniques is considered for a two-path Rayleigh-fading channel, and a semi-synchronous CDMA structure is proposed. It is shown that if maximum ratio combining (MRC) is employed, the decorrelating noise WF still exists. The corresponding suboptimal combining detector with a decorrelating noise WF outperforms a similar noncombining detector     

On the comparison between OFDM and single carrier modulation with aDFE using a frequency-domain feedforward filter

Most comparisons between single carrier and multicarrier modulations assume frequency-domain linear equalization of the channel. We propose a new frequency-domain decision feedback equalizer (FD-DFE) for single carrier modulation, which makes use of a data block transmission format similar to that of the orthogonal frequency-division multiplexing with cyclic prefix (OFDM). The scheme is a nonadaptive DFE where the feedforward part is implemented in the frequency domain, while feedback signal is generated by time-domain filtering. Through simulations in a HIPERLAN-2 scenario, we show that FD-DFE yields a capacity very close to that of OFDM. This result is also confirmed by analytical derivations for a particular case. Furthermore, when no channel loading is considered, FD-DFE performs closely to OFDM for the same averaged frame error rate in a coded transmission. Design methods of the FD-DFE are investigated and a reduced complexity technique is developed, with the result that FD-DFE and OFDM have a similar computational complexity in signal processing