Performance of iterative multiuser decoding and channel estimation in WCDMA systems

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).

In this paper we investigate the performance of a CDMA iterative multi-user receiver with non-binary modulation. The receiver incorporates iterative channel estimation and is applied to multipath fading channels. The particular algorithm investigated is an extension of the work presented in Alexander et al., (2000), and Grant et al., (2000). Results are presented based on analysis, simulation and fixed point DSP implementation.

This paper presents a novel iterative detection and channel estimation scheme that combines the effort of superimposed training (ST) and pilot-aided training (PAT) for multiple-input multiple-output (MIMO) flat fading channels. The proposed method, hereafter known as joint mean removal ST and PAT (MRST-PAT), implements an iterative detection and channel estimation that achieves the performance of data-dependent ST (DDST) algorithm, with the difference that the data arithmetic cyclic mean is estimated and removed from data at the receiver’s end. It is demonstrated that this iterative and cooperative detection and channel estimator algorithm surpasses the effects of data detection identifiability condition that DDST has shown when higher orders of modulation are used. Theoretical performance of the MRST-PAT scheme is provided and corroborated by numerical simulations. In addition, the performance comparison between the proposed method and different MIMO channel estimation techniques is analyzed. The joint effort between ST and PAT shows that MRST-PAT is a solid candidate in communications systems for multiamplitude constellations in Rayleigh fading channels, while achieving high-throughput data rates with manageable complexity and bit-error rate (BER) as a figure of merit.

The focus of this paper is the high mobility coded wireless communication system with Doppler diversity. In order to improve the bit-error-rate (BER) performance, we combine the systematic block Markov superposition transmission (BMST) with Doppler diversity, resulting in BMST-DD, where the systematic BMST is a recently proposed rate-compatible coding scheme. In the BMST-DD system, to reduce the performance loss caused by the channel estimation error, we propose an iterative channel estimation and decoding technique for the fast time-varying fading channels. In the iteration process, the recovered symbols are fed back to the channel estimator as the new pilot symbols to improve the accuracy of the channel state information (CSI) estimation. Numerical results show that the mutual information increases with the increase of the speed due to Doppler diversity, and that the BER performance of the BMST-DD system can be improved by the iteration between the channel estimator and the decoder.

This paper deals with a novel design approach for a converging iterative receiver for coded CDMA that estimates both the channel coefficients and the transmitted symbols. The receiver design is based on the variational Bayesian space-alternating generalized expectation-maximization (VB-SAGE) method. Conceptually, the probability distribution of each user's code sequence and the probability distribution of all channel coefficients are updated in an iterative fashion. The obtained receiver, which we refer to as VB-SAGE receiver, performs iterative channel estimation, interference cancellation and single-user decoding. Even though the design is based on code sequence probabilities, only the soft decisions (mean values) and the variances of the code symbols are required for channel estimation and interference cancellation; moreover, the variances are functions of the soft decisions. These soft decisions are computed by the single-user decoders based on the outputs of the interference cancellation device. The iterative process of the VB-SAGE receiver is guaranteed to converge in the free energy. The VB-SAGE method proposed in this paper may also be used for other applications.

The estimation of channel parameters, such as the fading amplitude and the power spectral density (PSD) of the interference and noise, is essential to the effective use of soft-decision decoding. Channel estimation may be implemented by the transmission of pilot signals that are processed by the receiver, but pilot signals entail overhead costs, such as the loss of data throughput. Deriving maximum-likelihood channel estimates directly from the received data symbols is often prohibitively difficult. There is an effective alternative when turbo or low-density parity-check codes are used. The expectation-maximization algorithm, which is derived and explained in this chapter, provides an iterative approximate solution to the maximum-likelihood equations and is inherently compatible with iterative demodulation and decoding. Two examples of advanced spread-spectrum systems that apply iterative channel estimation, demodulation, and decoding are described and analyzed. These systems provide good illustrations of the calculations required in the design of advanced systems.

We investigate the application of joint decoding and channel estimation for DS/CDMA transmission over slow Rayleigh fading channels. Some known symbols are inserted in the encoded data stream to enhance the channel estimation process. An iterative algorithm that uses the decoding information, in addition to the information contained in the known symbols, to improve the channel parameters estimate is proposed. A is shown that the optimum scheme has a complexity which grows exponentially with the channel estimation filter length. Hence, we propose some alternative sub-optimum schemes with polynomial complexity. The different techniques that provide a tradeoff between simplicity of implementation and BER performance are compared.

In order to increase the link capacity in the wideband direct sequence code division multiple access (W-CDMA) reverse link, employing a parallel-type coherent multistage interference canceller (COMSIC) is more practical than using a serial (successive)-type due to its inherent advantage of a short processing delay, although its interference suppression effect is inferior to the serial-type. Therefore, this paper proposes a parallel-type COMSIC with iterative channel estimation (ICE) using both pilot and decision-feedback data symbols at each canceling stage. Computer simulation results show that the required average transmit E/sub b//N/sub 0/ for obtaining the average BER of 10/sup -3/ using the three-stage parallel-type COMSIC with ICE using pilot and decision-feedback data symbols after forward error correction (FEC) decoding (number of iterations was 2 at each stage) was decreased by approximately 2.1 dB compared to a COMSIC with channel estimation using only pilot symbols, with the spreading factor (SF) of 16 and when the number of active users was 20 (thereby the capacity normalized by the processing gain (Pg) becomes 42%). The results also show that the required average transmit E/sub b//N/sub 0/, loss of the parallel-type COMSIC using ICE at the average BER of 10/sup -3/ compared to the serial-type was negligible (i.e., within 0.2 dB) due to the significantly improved channel estimation and decreased data decision error, while achieving a much shorter processing delay irrespective of the number of active users.

This paper analyzes the iterative channel estimation and multiuser detection in multipath fading coded CDMA channels. The maximum likelihood criterion is used for channel estimation while the interference is cancelled with direct interference cancellation. The channel decoder output is fed back to enhance the performance of the channel estimator and interference canceller. The asymptotic system performance is analyzed, and conditions for convergence and uniqueness of fixed point are given.

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.

In this paper, we extend the iterative demapping technique to observation separation (OS), which is an iterative channel estimation and symbol detection procedure. We consider a bit interleaved coded modulation with iterative decoding (BICM-ID) on a multipath channel with coded packet oriented transmission system with 16QAM. The channels considered are the time-invariant multipath and the channel estimation corresponds to the pseudo-inverse type. We propose here to study the influence of mapping over the performance of turbo equalization. Turbo equalization is a receiving process performing iteratively equalization and channel decoding; soft information generated by each receiving function is improved through the iterations until the optimum behavior of the system reached. In the studied system the turbo equalization and the channel estimation part is based on our previous work. In the context of bit interleaved coded modulation (BICM), the iterative demapping is an iterative process between the soft demapping device and the channel decoding. We analyze here the improvement of mapping optimization for turbo equalization and we proposed an optimized binary mapping of 16-QAM constellation in order to increase coding gain, which can be used for some practically important cases. It is demonstrated that owning to a carefully designed mapping, different to the classical Gray mapping, bit error rate performance is improved.

Channel estimation techniques for code-division multiple access (CDMA) systems need to combat multiple access interference (MAI) effectively. Most existing estimation techniques are designed for CDMA systems with short repetitive spreading codes. However, current and next generation wireless systems use long spreading codes whose period is much larger than the symbol duration. In this paper, we derive the maximum likelihood channel estimate for long code CDMA systems over multipath channels using training sequences and approximate it using an iterative algorithm to reduce the computational complexity in each processing window. The asymptotic convergence of the mean of the iterative estimate to the actual channel is also shown. The effectiveness of the iterative channel estimator is demonstrated in terms of squared error in estimation as well as the bit error rate performance of a multistage detector based on the channel estimates. Finally, the proposed iterative channel estimation technique is extended to track slowly varying multipath fading channels using decision feedback. Thus, an MAI resistant multiuser channel estimate with reasonable computational complexity is derived for long code CDMA systems over multipath fading channels.

In this chapter we investigate the tradeoff between channel estimation and channel diversity for channels with memory. Block memory channels are analytically tractable yet provide practical models for many communication systems. We show that for finite block length transmission techniques there is a fundamental tradeoff between the channel estimator and the channel diversity. When the channel is operating at rates much below capacity, smaller channel memory is better since channel estimation is not crucial. This is because the code contains more than adequate redundancy to compensate for mismatch due to the potentially poor channel estimate as well as channel errors. However, at rates close to capacity, channel state information is crucial for successful decoding and therefore longer channel memory, which allows better estimates, is better. We draw these conclusions based on analysis of some simple discrete-input, discrete-output channels using the channel reliability function and on simulation results for more realistic channels (soft output) using low-density parity check codes with a joint iterative decoder and channel estimator.

This work proposes a superimposed pilot (SP)-based channel estimation and data detection framework for orthogonal time-frequency space (OTFS) scheme, wherein low-powered pilots are superimposed on to data symbols in the delay-Doppler domain. We propose an iterative channel estimation and data detection design for SP-OTFS systems which, unlike the existing OTFS designs, does not designate any slots for pilots, which improves its spectral efficiency (SE). The proposed design iterates between message-passing-aided data detection and data-aided channel estimation. The data-detection and channel-estimation steps of the proposed design exploit the OTFS channel sparsity, which reduces its computational complexity. We numerically show that the proposed design has superior SE than the two state-of-the-art OTFS channel estimation and data detection designs.