Joint iterative channel estimation for space-time multiuser detection

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.

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 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.

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.

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 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.

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.

This paper deals with optimized Multiple-Input Multiple Output (MIMO) channel estimation and ensuing information throughput conveyed by pilot-based multi-antenna systems affected by both spatially colored Multiple Access Interference (MUI) and errors in the available channel estimates. The architecture of the Minimum Mean Square Error (MMSE) MIMO channel estimator is derived and the related analytical conditions for the optimal design of space-time training sequences are provided. Afterwards, closed form expressions for the maximum information throughput sustained by the considered systems for Gaussian distributed input signals are given and, then, a novel powers’ allocation algorithm for the asymptotical achievement of the system capacity is developed. Considerations about optimized space-division MAC strategies are also provided.

Intercarrier interference caused by fast time-varying multipath fading channels degrades the system performance of high-mobility orthogonal frequency division multiplexing systems. This study consi...

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.

The BER performance of concatenate block coded CDMA signal with coherent RAKE reception and complex spreading are considered in this paper. General multi-path intensity Nakagami fading and multiple-access near/far interference channel are assumed. A dedicated pilot channel for coherent demodulation is used for the purpose of channel estimation. Pilot channel estimation error, due to multiple-access interference and multi-path fading is studied. The analysis for system performance shows that the error of channel estimation significantly degrades BER performance and can be effectively suppressed by serial concatenate block code (SCBC) and parallel concatenate block code (PCBC) schemes. Also in this paper, an attempt for comparing the BER on different concatenate block coding schemes has been made. And a discussion on the multiple-access near/far interference is also included, which illustrates that it can be effectively limited by power control and SCBC/PCBC schemes.KeywordsChannel EstimationBlock CodeCode WordMaximum Ratio CombinePilot SymbolThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Continuous-phase frequency shift keying (CPFSK) is a type of frequency shift keying (FSK) that maintains phase continuity from symbol to symbol. The bandwidth efficiency of a CPFSK waveform is characterized by its modulation index, number of frequency tones and channel coding rate. These parameters can be flexibly designed to meet different bandwidth and energy requirements in wireless communication systems. One special case of CPFSK, orthogonal FSK, could be applied when bandwidth constraints are loose. By increasing the number of frequency tones, the energy efficiency can be improved at the expense of spectral efficiency. In this dissertation, the general case of orthogonal FSK, orthogonal modulation is first studied. Capacity, convergence behavior and asymptotic error rates of coded orthogonal modulation are analyzed. In addition to coherent detection, we consider noncoherent detection as well, which is one benefit of CPFSK. More often, CPFSK is designed to achieve high spectral efficiency by reducing its modulation index. The general case of nonorthogonal CPFSK is then studied. Capacity, spectral efficiency and capacity approaching code design are discussed for both coherent and noncoherent CPFSK. In addition to the system design and information theoretic issues, channel estimation for noncoherent CPFSK is considered. An iterative channel estimation, demodulation and decoding algorithm is derived using the expectation maximization (EM) algorithm. Finally, we apply noncoherent CPFSK to frequency hopping (FH) networks, leveraging the results acquired throughout the dissertation. Simulations show FH networks with CPFSK modulation and channel estimation can achieve robust performance against partial-band and multiple-access interference.

In this paper, while considering the impact of antenna correlation and the interference from neighboring users, we study the problem of channel estimation and training sequence design in multi-input multi-output (MIMO) two-way relaying (TWR) systems. To this end, we propose to decompose the bidirectional transmission links into two phases, i.e., the multiple access (MAC) and the broadcast (BC) phases. By deriving the optimal linear minimum mean-square-error estimators, the corresponding training design problems for the MAC and BC phases are formulated and solved. Subsequently, algorithms and, in some special cases, closed-form solutions for obtaining the optimal training sequences for channel estimation in TWR systems are derived. Moreover, to further reduce channel estimation overhead, the minimum required length of the training sequences are determined. Simulation results verify the effectiveness of the proposed training designs in improving channel estimation performance in TWR systems.

Channel estimation is critical to coherent RAKE receiver performance. This paper deals with channel estimation based on the standard algorithm suggested for UTRA-TDD by 3GPP. It proposes a spatial pre-combination technique that exploits the spatial structure of the received multipath signal to improve the channel estimator performance. Self and multiple access interference is partially cancelled before the channel estimation algorithm. The performance of the estimation algorithm is assessed by resorting to simulations in typical UMTS-TDD scenarios and the correlation coefficients between the complex channel and the estimates are computed. The effect of imperfect channel estimation on the performance of RAKE1D and RAKE2D receivers is analyzed in a multiuser scenario.

Channel estimation in low SNRs is challenging for multiple-input multiple-output single carrier frequency domain equalization (MIMO SC-FDE) systems. This paper presents a novel design of training sequences with circular orthogonal properties, which can be applied to accurate channel estimation. The orthogonality of training sequences help to eliminate the interference between the transmit antennas, while circular orthogonality guarantees the identification of every resolvable delay bin of each multipath channel at the receiver. Compared to the traditional frequency-domain channel estimation methods, the proposed algorithm not only suppresses the interference between the antennas but also decreases the variance of the noise, resulting in the improvement in MSE of channel estimation and BER performance of the system. Simulation results demonstrate the effectiveness and feasibility of the proposed algorithm.