Iterative channel estimation and multiuser detection in multipath CDMA channels

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.

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.

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.

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.

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 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).

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

In this paper, anew iterative interference cancellation multiuser detection (MUD) method is proposed for overloaded multiple-input multiple-output (MIMO) coded orthogonal frequency division multiplexing (OFDM) systems. In the first iteration, a channel analyzer and selector are employed, which ensure that non-convergent channels are not used. Then low complexity RAKE reception is applied, and a successive interference cancellation (SIC)-based approach is used such that the strongest user is decoded first. In each iteration, the soft output of the convolutional decoder is fed back to cancel inter-user interference using parallel interference cancellation (PIC). The simulation results show that, this technique can achieve near-optimum bit error rate (BER) performance, and optimum frame error rate (FER) performance, with lower complexity than optimum maximum likelihood (ML) methods at the cost of 4% of channels rejected.

In this paper we derive a novel extrinsic information transfer (EXIT) function for a channel estimator that uses both pilot symbols and soft decoding information. We consider a CDMA system with forward error correction that employs iterative multiuser detection based on soft interference cancellation and single user decoding. The J function is useful in convergence analysis as it provides a mapping between mutual information and variance. J functions are derived for both the flat-fading Rayleigh channel and channel estimate, allowing the a priori inputs to the channel estimator, interference canceller and decoder to be modeled. Algorithms for obtaining the EXIT functions for the three receiver blocks are proposed. We then combine the EXIT functions to create an EXIT chart that can be used to predict the behaviour of the overall receiver. Simulations are run for a 3GPP-like receiver in a mobile environment with a vehicle speed of 100 km/h. It is found that under these conditions, the detector trajectory closely matches our proposed EXIT chart.

Due to the scarcity and high cost of satellite frequency spectrum, it is very important to utilize the available spectrum as efficiently as possible. The efficient usage of the spectrum in the satellite return link is a challenging task, especially if multiple users are present. In previous works Multi-User Detection (MUD) techniques have been widely studied to increase the spectral efficiency of the satellite return link. However, due to the high computational complexity and its sensitivity to synchronization and channel estimation errors, only few implementations of MUD for satellite communications exist. In this paper a novel Graphics Processing Unit (GPU)-based Software Defined Radio (SDR) implementation of a MUD receiver for transparent satellite return link is presented, which uses iterative channel estimation and decoding. The implementation can cope with the presence of strong phase noise. In addition to its high flexibility and low cost, with the GPU acceleration our SDR MUD receiver implementation achieves a decoding throughput of 270 Kbps using a single GPU card.

This paper studies the performance of iterative multiuser decoding, interference cancellation, and channel estimation techniques applicable to third generation WCDMA systems. The concept uses a posteriori probabilities of code symbols to enhance detection, decoding and channel estimation in an iterative fashion. The performance is analyzed in a multipath channel with simulations. It is seen that the proposed concept combats multiuser interference effectively and performs almost as well as single user systems.

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.

FBMC is a pivotal system in 5G, serving as a cornerstone for efficient use of available bandwidth while simultaneously meeting stringent requirements for high spectral efficiency. Notably, FBMC harnesses the power of multicarrier modulation (MC), a good alternative to orthogonal frequency division multiplexing (OFDM) technology that supports fourth-generation (4G) systems. The wireless communications field is full of challenges, the most important of which are channel estimation and interference cancellation, both of which deserve comprehensive study to increase the efficiency of data transmission. In this paper, our investigation takes a deliberate step towards the convergence of two prominent modulation models: OFDM and FBMC. We specifically contrast these modulation techniques with the intricate field of joint channel estimation and interference cancellation (JCEIC). In this research study, we take advantage of recurrent neural networks' (RNNs') efficiency as a vehicular channel to perform precise channel estimation and recovery of uncorrupted transmitted signals, thereby lowering the bit error rate (BER). Our channel estimation for a dual selective channel is based on the thoughtful placement of pilots scattered over the temporal and frequency dimensions, and is further improved by the interference cancellation method of low complexity that was selected. Our JCEIC proposal aims to integrate RNNs carefully, using the output sequences of JCEIC algorithms as useful inputs to this neural architecture. By clearly demonstrating a decrease in BER as compared to traditional approaches, it is evident that the performance of the novel approach is near to that of a perfect channel. Additionally, a comparison of the performance of FBMC and OFDM systems at various signal-to-noise ratios reveals a clear performance divide that favors the former in terms of system efficiency. The BER is restricted by FBMC to a commendable threshold of less than 0.1 at a modest 5 dB, continuing the higher trend started by its improved RNN-based channel estimate. The accuracy of channel estimation is clearly improved by this paradigm shift, and the computing complexity typical of 5G networks is also clearly reduced.

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.

We propose an application for Observation Separation (OS), which is an iterative channel estimation and symbol detection procedure by using the training sequence and the decoded data, on a multi-path channel with coded packet oriented transmission system with a high level modulation M-QAM (M=2 m ). The channel considered is a time-invariant multi-path (1) and the channel estimation cor- responds to the pseudo-inverse type. For every symbol, the detection takes into account just the part of observation, which contains the considered symbol and has length corresponding to the channel memory length. The detection techniques used are the Zero Forcing Block Linear Equalizer (ZF-BLE) for the initial iteration and Interference Cancellation (IC) for the other iterations. For the feedback loop, the hard or soft decision of the channel decoder output is employed.