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In this paper, we consider pilot-aided channel estimation and equalization for single-carrier and single-carrier frequency division multiple-access (SC-FDMA) transmission over doubly-selective channels (DSC). To reduce the channel estimation (CE) parameters, the DSC is modelled using a complex-exponential basis expansion model (CX-BEM) with non-uniform BEM frequencies. We optimize the CX-BEM basis functions using CE error minimization as the objective. As a result, the channel modelling error is greatly reduced. Next, we propose a BEM-based per-survivor processing (PSP) technique and combine it with a decision-directed channel estimator to obtain a channel-tracking equalizer at the receiver. The resultant BEM-PSP receiver significantly improves the channel estimation mean square error (MSE) and the bit error rates (BER) performance in fast fading multi-path channel, thanks to the channel tracking capability embedded within its Viterbi equalizer. Finally, we employ cross-frame channel interpolation, and power distribution between the data and pilot symbols to further improve the system performance at high fading rates. Extensive simulation results show that our BEM-PSP receiver outperforms many existing methods and approaches close to an ideal receiver with perfectly known CSI under various fading scenarios. Nanyang Technological University This work was supported by the NRF–NSFC Project under Grant NRF2016NRF-NSFC001-089. The work of Xiaobei Liu and Yong Liang Guan was supported by Temasek Laboratories, NTU, through the Signal Research Programme 3 under Grant DSOCL17187. The work of Pingzhi Fan was supported in part by the NSFC Project under Grant 61661146003 and Grant 61731017, and in part by the 111 Project under Grant 111-2-14. The work of Zhengchun Zhou was supported in part by the Application Fundamental Research Plan Project of Sichuan Province under Grant 2018JY0046.

This paper investigates pilot design for enhanced channel estimation in single carrier communication systems over doubly-selective channels (DSC). Our contribution is twofold: first, we propose to use Huffman sequences as pilot clusters with low peak-to-average power ratio (PAPR), yet with good channel estimation performance when periodic pilot placement is adopted; second, we propose a low-complexity pilot placement strategy based on the analysis of the complex-exponential basis expansion model (CE-BEM) of the DSC. The latter leads to improved channel estimation performance with useful insights for pilot placement. Nanyang Technological University National Research Foundation (NRF) This work was supported by the NRF-NSFC project under Grant NRF2016NRF-NSFC001-089. The works of Y. L. Guan and X. Liu were supported by Temasek Laboratories@NTU Signal Research Programme 3 Grant.

In this paper, the problem of blind multi-user detection (MUD) of co-frequency phase-shift keying (PSK) signals with unknown carrier frequency offsets (CFOs) is investigated. Firstly, a CFO estimation scheme which explores cyclic-feature of the received mixture signal to estimate CFOs of signals from different users is introduced. After that, a CFO-robust turbo MUD detector which performs blind channel estimation and symbol detection iteratively is proposed. Simulation results show that by using the proposed blind turbo MUD receiver, the symbol error rates (SERs) of the detected symbols are much lower than those achieved by using the conventional MUD receiver, and the SER obtained by the blind MUD receiver is very close to SER obtained under perfect channel state information (CSI) condition.

Single-channel blind source separation (SCBSS) of uncoordinated, non-spread, co-frequency interfering signals with non-zero carrier frequency offset and timing offset, and without training sequence for channel estimation, is a challenging task. Iterative SCBSS of coded signals leads to good performance but is computationally expensive as it involves the turbo processing of multi-user per-survivor processing and soft-input soft-output channel decoding. In this letter, we propose a low-complexity SCBSS (LC-SCBSS) scheme, which reduces the computational complexity of the conventional iterative SCBSS by using interference-cancellation from the second iteration onward, and adaptive channel truncation for certain users. Simulation results show that the proposed LC-SCBSS reduces the computational complexity by more than 99%, with only a marginal degradation in performance. Accepted version

In this paper, the reconstruction of the feedback polynomial as well as the initial state of a linear feedback shift register (LFSR) in a synchronous scrambler placed after a channel encoder is studied. The study is first based on the assumption that the channel is noiseless and then extended to the noisy channel condition. The dual words, which are orthogonal to the codewords generated by the channel encoder, are used in the reconstruction algorithm. The number of bits required by the new algorithm is compared with another recently proposed algorithm and results show that the number of bits required to do the reconstruction can be significantly reduced.

Turbo equalization is an iterative approach to perform joint equalization and decoding of data, which is protected by error correction code and transmitted over intersymbol interference (ISI) channels. Turbo equalization for Reed Solomon (RS) code, which is a popular error-correction code in wireless communication and recording systems, is seldom discussed in the literature. In this paper, we investigate the computational complexity and performance of turbo equalization which exploits three different kinds of equalization algorithms, i.e., BCJR, M-BCJR and linear minimum mean square error (LMMSE) algorithms. An adaptive belief propagation (ABP) algorithm is used for the decoding of RS code. Simulation results show that, the complexities of the LMMSE and M-BCJR based equalizers are much lower than that of the BCJR based equalizer, and at the same time the performance loss is still acceptable.

Joint source channel decoding (JSCD) for variable length codes (VLCs) has been shown to be effective for error- prone channels. In this paper, we propose two schemes to enhance the performance of the existing bit-based JSCD approach for VLCs. Simulation results show that the performance of the decoder can be significantly improved, while the computational complexity is only slightly increased by using our proposed schemes.

A joint source-channel decoding (JSCD) scheme which exploits the combined a priori information of source and channel in an iterative manner is proposed. A sequence minimum mean-square error (SMMSE) estimator based on bit or symbol error transition probability of the channel with memory is proposed and used in the iterative decoding process. Simulation results show that our proposed scheme leads to significant improvement over the scheme without using the a priori information of the source or channel.

An adaptive blind multiuser detection algorithm is proposed for asynchronous direct-sequence code-division multiple-access (DS-CDMA) systems based on a modified constrained Kalman filter over a multipath fading channel. This detector is shown to outperform the present least mean squares filter in bit-error-rate and convergence rate, and it is shown to have a better tracking capability under a dynamic environment where the number of users will change frequently with time.

A joint source channel coding (JSCC) scheme which exploits bit-level correlation as well as symbol-level correlation efficiently in a source-controlled channel decoding (SCCD) process is proposed and applied to the mixed-excitation linear prediction (MELP) parameters of speech. A modified BCJR algorithm is also proposed for use in the SCCD algorithm. Simulation results show that our proposed scheme performs better than other redundancy-based JSCC schemes such as bit-based SCCD, soft-bit speech decoding (SBSD) and iterative source-channel decoding.

In this paper, the problem of reconstruction of the feedback polynomial in a linear scrambler is studied. Our work contains two parts. In the first part, schemes to improve the performance of an existing reconstruction algorithm are proposed. Simulation results show that both the detection capability and speed of the existing algorithm are significantly improved by using our proposed schemes. In the second part, the reconstruction of linear scramblers in the presence of channel noise is investigated. We consider flipped bits due to noise as well as insertion of bits in the scrambled bit sequence. For both cases, factors which affect the performance of the reconstruction algorithm are discussed. Accepted version

The paper presents memory-enhanced extensions of minimum mean-squared error (MMSE) decoding for vector quantization over noisy channels. We also develop a recursive algorithm for computing the transition probabilities of the Gilbert channel, and illustrate its performance in vector quantization of Gauss-Markov sources under noisy channel conditions. Simulation results indicate that the proposed algorithm enables the implementation of an MMSE decoder with increased robustness to channel errors.