Iterative joint detection, decoding, and channel estimation for dual antenna arrays in frequency selective fading

In this paper, we propose a receiver structure that performs joint iterative multiuser detection and channel estimation for the uplink of differentially coded asynchronous direct-sequence code-division multiple-access systems in unknown multipath channels. The overall transmission scheme for each user is the serial concatenation of a recursive systematic convolutional (RSC) encoder and a differential encoder separated by an interleaver. The proposed receiver consists of two stages. The first stage performs channel estimation, soft interference cancellation, and soft-input soft-output multiuser filtering, followed by the second stage, which consists of a bank of serially concatenated single-user channel decoders and differential decoders. The single-user iterative decoder for each user consists of a powerful combination of an RSC decoder and a differential decoder, which work together in an iterative fashion. In terms of channel estimation, at the first iteration, the multipath channel is blindly estimated by exploiting the orthogonality property between the signal and noise subspaces, whereas, for the next iterations, the channel is estimated using the soft estimates of coded bits of each user provided by the single-user iterative decoders in conjunction with the output of the multiuser detector. By exchanging soft information between the different stages, the receiver performance is improved through iteration. Simulation results demonstrate that the performance of the proposed iterative multiuser detector with the integrated channel estimator approaches the single-user bound at high signal-to-noise ratio.

We propose a layered space time (LST) transceiver in a multiuser code division multiple access (CDMA) mobile communication system. In particular, we examine a multiuser iterative receiver with joint detection, channel estimation and decoding in a frequency selective fading channel. The iterative parallel interference canceller (PIC) with statistics combining is used as the multiuser detection scheme and a least mean square (LMS) adaptive algorithm is applied to estimate the multiple input and multiple output (MIMO) frequency selective fading channel. Simulation results are presented to demonstrate the performance of this receiver. It is shown that the performance of the receiver with iterative channel estimation is close to that of the receiver with perfect channel state information (CSI).

Signals transmitted over a land mobile radio channel are very often subjected to frequency selective fading. A detection technique is proposed for continuous phase modulation (CPM) operating in such an environment. The technique uses embedded pilot symbols for channel impulse response estimation. The estimated channel response is updated from symbol to symbol and is used during the sequence detection of the CPM signal. Unlike pilot symbol assisted linear modulation, the pilot symbols in this CPM system are divided into two groups. The first group of pilot symbols is data-dependent and is used to force the modulator to return periodically to a known system state. The second group is not data-dependent and is used to specify a known waveform emanating from the periodic known state, for the purpose of channel estimation. The proper pilot symbol encoding rules, as well as the structure of the companion channel estimator, are presented. It is shown that CPM schemes employing this detection technique exhibit no irreducible error floor even in the presence of fast fading and large delay spread. The modem actually performs better in a heavily frequency selective fading environment, due to the implicit diversity effect provided by the channel. The difference in energy efficiency between frequency selective and flat fading can be as large as 5 dB at a 10-3 bit error rate and 8 dB at a 10-4 error rate. These results suggest that the proposed technique is very suitable for use in a system which employs diversity.

To mitigate the inter-chip and inter-symbol interferences (ISI), multi-carrier code-division multiple access (MC-CDMA) communication systems, which integrate the advantages of multi-carrier transmission systems with those of CDMA, are considered as promising techniques for future broadband wireless multimedia communications. In this paper, we focus on the uplink multi-user detection (MUD) on the scheme that a uniform linear array (ULA) is applied to the base station of the MC-CDMA system. We first describe the equivalent spatial-temporal channel model of multi-user multiple-input multiple-output (MIMO) MC-CDMA systems. Based on this scheme, by utilizing the finite alphabet property of transmitted symbols, an multi-user detector is derived for the MC-CDMA system with the ULA over frequency-selective fading channels. Computer simulations illustrate that our algorithm is more robust against noise and can well mitigate multiple access interference (MAI) in multi-user scenarios. In particular, the proposed scheme has the potential of providing the anticipated MUD performance gains with a complexity that would be manageable for MC-CDMA systems.

This work examines the use of two-way training to efficiently discriminate the channel estimation performances at a legitimate receiver (LR) and an unauthorized receiver (UR) in a multiple-input multiple-output (MIMO) wireless system. This work improves upon the original discriminatory channel estimation (DCE) scheme proposed by Chang where multiple stages of feedback and retraining were used. While most studies on physical layer secrecy are under the information-theoretic framework and focus directly on the data transmission phase, studies on DCE focus on the training phase and aim to provide a practical signal processing technique to discriminate between the channel estimation performances (and, thus, the effective received signal qualities) at LR and UR. A key feature of DCE designs is the insertion of artificial noise (AN) in the training signal to degrade the channel estimation performance at UR. To do so, AN must be placed in a carefully chosen subspace, based on the transmitter's knowledge of LR's channel, in order to minimize its effect on LR. In this paper, we adopt the idea of two-way training that allows both the transmitter and LR to send training signals to facilitate channel estimation at both ends. Both reciprocal and nonreciprocal channels are considered and a two-way DCE scheme is proposed for each scenario. For mathematical tractability, we assume that all terminals employ the linear minimum mean square error criterion for channel estimation. Based on the mean square error (MSE) of the channel estimates at all terminals, we formulate and solve an optimization problem where the optimal power allocation between the training signal and AN is found by minimizing the MSE of LR's channel estimate subject to a constraint on the MSE achievable at UR. Numerical results show that the proposed DCE schemes can effectively discriminate between the channel estimation and, hence, the data detection performances at LR and UR.

This paper studies the pilot design for compressed sensing (CS)-based sparse channel estimation in multi-input–multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. To improve the performance of estimating multiple jointly sparse channels, based on the assumption that the modulus of the pilot symbol at each pilot carrier position is equal to a constant, the pilot is currently allocated by means of lowering the sensing matrix’s total coherence (TC). However, according to the block compressed sensing (BCS) theory, the recovery ability of the sensing matrix is determined by the block coherence (BC) and subblock coherence (SC), which should be as small as possible. Therefore, we propose a novel scheme, which designs the pilot by simultaneously minimizing the TC, BC, and SC of the sensing matrix to improve the channel estimation accuracy. We first formulate the jointly sparse channel estimation as a block sparse signal recovery problem, and the pilot allocation problem is comprised of allocating the pilot index for each transmitter and allocating the pilot symbol at each carrier. Then, we derive the error bound of BCS-based channel estimation, where the pilot symbols bear any value. Finally, a novel sequential joint criterion design (SJCD) method is proposed to design pilots with a joint criterion, where the pilot pattern and pilot power are designed by BC and TC, respectively. Simulation results show that, compared with existing algorithms, the proposed algorithm can achieve a better channel estimation performance in terms of normalized mean square error (NMSE) and bit error rate (BER).

A method for coherently detecting and decoding turbo-coded binary phase shift keying (BPSK) signals transmitted over frequency-flat fading channels is discussed. Estimates of the complex channel gain and variance of the additive noise are derived first from known pilot symbols and an estimation filter. After each iteration of turbo decoding, the channel estimates are refined using information fed back from the decoder. Both hard-decision and soft-decision feedback are considered and compared with three baseline turbo-coded systems: (1) a BPSK system that has perfect channel estimates; (2) a system that uses differential phase shift keying and hence needs no estimates; and (3) a system that performs channel estimation using pilot symbols but has no feedback path from decoder to estimator. Performance can be further improved by borrowing channel estimates from the previously decoded frame. Simulation results show the influence of pilot symbol spacing, estimation filter size and type, and fade rate. Performance within 0.49 and 1.16 dB of turbo-coded BPSK with perfect coherent detection is observed at a bit-error rate of 10/sup -4/ for normalized fade rates of f/sub d/T/sub s/=0.005 and f/sub d/T/sub s/=0.02, respectively.

A novel Multiuser Detection (MUD) scheme is proposed for DS-CDMA systems employing the so-called Harmony Search (HS) algorithm, which is a novel meta-heuristic optimisation method. We specifically design the HS aided MUD for the communications problem considered and apply it in an iterative joint Channel Estimation (CE), MUD and channel decoding framework. The simulation results demonstrate that a near-single-user performance can be achieved by the proposed algorithm while avoiding the excessive-complexity full-search-based optimum detection even in overloaded DS-CDMA systems. Moreover, the HS algorithm can be efficiently applied in the Expectation Maximisation (EM) based CE framework.

In this paper, a pilot-assisted minimum mean square error (MMSE) multiuser channel estimation algorithm is proposed for quasi-synchronous code-division multiple-access (CDMA) systems that undergo frequency-selective channel fading. The frequency-selective multiuser fading channel is represented as a symbol-wise time-varying chip-spaced tapped delay line filter with correlated filter taps. The multiuser channel tap coefficients at pilot symbol positions are estimated under the MMSE criterion with the help of the channel intertap correlation matrix, which is determined by the combined effects of the physical fading channel, transmit filter, and receive filter. In the development of the estimation algorithm, the channel intertap correlation matrix is deemed as an essential factor, and a novel iterative method is proposed for the joint estimation of the channel intertap correlation and filter tap timing based on the received pilot samples. Simulations show that the information of the channel intertap correlation is critical to the performance of the channel estimation, and the channel taps at different delays cannot be assumed uncorrelated for CDMA systems experiencing frequency-selective fading.

In this paper, we investigate the convergence behavior of code-aided channel estimation, also denoted as joint iterative channel estimation and decoding. A mutual information transfer chart is introduced in order to trace the information exchange between channel estimator and decoder throughout the iterative process. Furthermore, a heuristic concept to improve code-aided channel estimation is introduced that outperforms the classical concepts and has the major advantage that it allows for accurate convergence analysis.

This study proposes an efficient channel-estimation scheme for Multiband (MB) Orthogonal Frequency Division Multiplexing (OFDM)-based Ultra Wide Band (UWB) communication systems. One of the challenges in wireless system is the frequency selective fading caused due to multipath channel between the transmitter and receiver. The signal bandwidth in broad band cellular wireless systems typically exceeds the coherence bandwidth of the multipath channel. To overcome such a multipath fading environment with low complexity and to increase the performance, UWB OFDM system is used. To practically realize MB-OFDM UWB, one needs to cope with numerous design challenges, particularly in receiver designs such as symbol timing, Carrier Frequency Offset (CFO) and sampling frequency offset compensation, as well as Channel Frequency Response (CFR) estimation. A channel estimation scheme using a Takagi-Sugeno (T-S) fuzzy based neural network under the time varying velocity of the mobile station in a UWB OFDM system is proposed in this study. In our proposal, by utilizing the learning capability of Adaptive Neuro-Fuzzy Inference System (ANFIS), the ANFIS is trained with correct channel state information then the trained network is used as a channel estimator. To validate the performance of our proposed method, simulation results are given and found that it gives more accurate prediction of channel coefficients as compared with fuzzy channel estimator under various highly noisy multipath channel conditions.

Blind estimation of time-varying single-input-multiple-output (SIMO) channel in the presence of cochannel interference (CI) is approached. The method consists of two-stages, i.e., initial estimation with the channel equalization matrix, and alternate estimation of the signals and the channel matrix by utilizing the finite alphabet property of transmitted signal. The computer simulations have shown the effectiveness of the algorithm when applied to the blind processing of the received signals through the frequency selective multipath fading channel and with CI.

Joint iterative channel estimation and decoding for 16-QAM bit-interleaved coded modulation (BICM) is considered over frequency-flat fading channels. Estimates of the complex channel gain are derived first from known pilot symbols by optimum Wiener filtering and passed to the BICM iterative decoder as initial channel state information. After each decoding iteration, the channel estimates are refined using the extrinsic information fed back from the decoder. An advanced scheme called restart is developed to effectively reduce the bit error rate floor, by restarting the decoder after several iterations with the refined channel gain estimates. Motivated by the observation of the burst errors in the transmitted sequence, the restart algorithm is extended by concatenating Reed-Solomon codes with BICM. When RS (255, 223) code is used for BICM with 16-QAM modified set partitioning labeling and a 16-state code, the BER of 10/sup -6/ can be achieved at E/sub b//N/sub 0/ of 10.5 dB for normalized fade rate f/sub d/T/sub s/ = 0.02.

There is a demand for high data rate wireless communications over channels which are subject to both time selective and frequency selective fading. To obtain low error rate communications over these channels with the previously proposed channel estimation methods requires a large proportion of the transmitted signal to be dedicated to pilots and/or extensive computations in the radio receivers. This paper proposes a joint channel estimation and data detection system based on two Kalman filters. One Kalman filter is used to estimate the channel state while the second Kalman filter is used for signal equalization. An iterative procedure is used to allow for accurate data detection without requiring a high proportion of pilots. In each iteration of the receiver, the detected symbol sequence from the previous iteration is used as a virtual pilot signal to improve the accuracy of channel estimation. This paper demonstrates that this iterative receiver with two Kalman filters achieves an E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</sub> /N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> versus BER performance within 1 dB of radio receivers operating with ideal channel gain information in the presence of channel fading rates as high as 1% of the symbol rate. The computational cost of the proposed receiver algorithm is of the same order of magnitude as currently deployed receiver algorithms, making this algorithm feasible for implementation.

This paper examines the performance of decision-feedback-based iterative channel estimation and multiuser detection in channel coded aperiodic direct sequence code division multiple-access systems operating over multipath fading channels. First, explicit expressions describing the performance of channel estimation and parallel interference-cancellation-based multiuser detection are developed. These results are then combined to characterize the evolution of the performance of a system that iterates among channel estimation, multiuser detection and channel decoding. Sufficient conditions for convergence of this system to a unique fixed point are developed