Jun Tong

The OFDM-IDMA approach to wireless communication systems

This article outlines the basic principles of OFDM-IDMA. Comparisons with other alternative technologies such as OFDM-CDMA and OFDMA are provided. Some attractive features of OFMD-IDMA are explained, including low-cost iterative multi-user detection, flexible rate adaptation, frequency diversity, and significant advantages regarding spectral and power efficiency.

Analysis and optimization of CDMA systems with chip-level interleavers

In this paper, we present an unequal power allocation technique to increase the throughput of code-division multiple-access (CDMA) systems with chip-level interleavers. Performance is optimized, respectively, based on received and transmitted power allocation. Linear programming and power matching techniques are developed to provide solutions to systems with a very large number of users. Various numerical results are provided to demonstrate the efficiency of the proposed techniques and to examine the impact of system parameters, such as iteration number and interleaver length. We also show that with some very simple forward error correction codes, such as repetition codes or convolutional codes, the proposed scheme can achieve throughput reasonably close to that predicted by theoretical limit in multiple access channels.

Superposition coded modulation and iterative linear MMSE detection

We study superposition coded modulation (SCM) with iterative linear minimum-mean-square-error (LMMSE) detection. We show that SCM offers an attractive solution for highly complicated transmission environments with severe interference. We analyze the impact of signaling schemes on the performance of iterative LMMSE detection. We prove that among all possible signaling methods, SCM maximizes the output signal-to-noise/ interference ratio (SNIR) in the LMMSE estimates during iterative detection. Numerical examples are used to demonstrate that SCM outperforms other signaling methods when iterative LMMSE detection is applied to multi-user/multi-antenna/multipath channels.

Analysis and design of OFDM-IDMA systems

SUMMARY This paper deals with the analysis and design of orthogonal frequency-division multiplexing interleavedivision multiple-access (OFDM-IDMA). We begin with the analysis of the information-theoretical advantages of non-orthogonal transmission schemes in fading multiple-access channels. We then turn attention to practical design issues. A signal-to-noise ratio (SNR) evolution technique is developed to predict the bit-error-rate (BER) performance of OFDM-IDMA. This technique is applied to system design and optimisation. Through proper power allocation, OFDM-IDMA can achieve the multi-user gain (MUG) predicted by information-theoretical analysis. It is also an attractive option in compensating for the clipping effect caused by peak-power limitation. Numerical examples show that OFDM-IDMA can (i) alleviate the PAPR problem commonly suffered by OFDM-based schemes; (ii) deliver significant MUG compared with other orthogonal alternatives; (iii) provide robust communications in frequency-selective channels; and (iv) support high single-user throughput. Copyright

Superposition Coded Modulation With Peak-Power Limitation

We apply clipping to superposition coded modulation (SCM) systems to reduce the peak-to-average power ratio (PAPR) of the transmitted signal. The impact on performance is investigated by evaluating the mutual information driven by the induced peak-power-limited input signals. It is shown that the rate loss is marginal for moderate clipping thresholds if optimal encoding/decoding is used. This fact is confirmed in examples where capacity-approaching component codes are used together with the maximum a posteriori probability (MAP) detection. In order to reduce the detection complexity of SCM with a large number of layers, we develop a suboptimal soft compensation (SC) method that is combined with soft-input soft-output (SISO) decoding algorithms in an iterative manner. A variety of simulation results for additive white Gaussian noise (AWGN) and fading channels are presented. It is shown that with the proposed method, the effect of clipping can be efficiently compensated and a good tradeoff between PAPR and bit-error rate (BER) can be achieved. Comparisons with other coded modulation schemes demonstrate that SCM offers significant advantages for high-rate transmissions over fading channels.

Iterative Soft Compensation for OFDM Systems with Clipping and Superposition Coded Modulation

This paper deals with the clipping method used in orthogonal frequency-division multiplexing (OFDM) systems to reduce the peak-to-average power ratio (PAPR). An iterative soft compensation method is proposed to mitigate the clipping distortion, which can outperform conventional treatments. The impact of signaling schemes on the residual clipping noise power is studied via the symbol variance analysis. It is found that superposition coded modulation (SCM) can minimize the residual clipping noise power among all possible signaling schemes. This indicates that SCM-based OFDM systems are more robust to clipping effect than other alternatives when soft compensation is applied. It is also shown that a multi-code SCM scheme can further reduce the clipping effect and its overall performance can be quickly evaluated using a semi-analytical evolution method. Numerical examples are provided to verify the analysis.

Superposition Coding with Peak-Power Limitation

This paper presents a peak-power-limited superposition coding scheme based on clipping. A low-complexity soft compensation algorithm (SCA) for combating the clipping effect is investigated. It can be easily combined with soft-input soft-output (SISO) decoding algorithms in an iterative manner. Various numerical results show that the SCA can effectively mitigate the performance loss due to clipping.

Performance Analysis of OFDM-IDMA Systems with Peak-Power Limitation

This paper is concerned with orthogonal frequency- division multiplexing interleave-division multiple-access (OFDM- IDMA) systems over frequency-selective fading channels. Deliberate clipping is applied to reduce the peak-to-average power ratio (PAPR) of each users transmitted signal. An iterative multiuser detection (MUD) technique is developed to recover the performance loss due to clipping. A semi-analytical signal-to- noise ratio (SNR) evolution technique is proposed, which can provide quick and accurate prediction of the iterative MUD performance. Numerical results show that the performance of OFDM-IDMA is not sensitive to the frequency selectivity of channels, and OFDM-IDMA is more power-efficient than other alternative multi-carrier transmission techniques.

Design and Analysis of Large MIMO Systems With Krylov Subspace Receivers

This paper studies large multiple-input multiple-output (MIMO) communication systems with linear precoding and reduced-rank Krylov subspace receivers. We design precoders and analyze their performance by exploiting large-dimensional random matrix theory. We first devise low-complexity precoding schemes that can improve performance of low-rank Krylov subspace receivers in the regime of high signal-to-noise ratio (SNR). We then introduce a potential theory-based method for analyzing the convergence behavior of the mean-squared error (MSE) for various transmission schemes. This method can be applied to a broader range of problems compared to previous analytical tools. The analysis reveals that the MSE decreases super exponentially with the rank of the receiver. Numerical examples show that the proposed precoders can outperform conventional precoders when low-rank Krylov subspace receivers are used, and that the performance of such receivers can be accurately predicted.

Review: A unified framework for regularized linear estimation in communication systems

Two concerns often arise simultaneously when applying linear estimation in communication systems: the computational complexity can be prohibitively high when the system size is large, and the performance may degrade dramatically when the presumed model is mismatched with the actual system. In this paper, we introduce a subspace expansion framework to jointly address these concerns, in which the observation is first projected onto a lower-dimensional subspace and then the solution of the projected problem is regularized. We discuss two projection methods based on eigensubspace and Krylov subspace expansions. We show that the Krylov subspace projection provides an economical solution to regularized linear estimation. We also compare different regularization methods, such as principal components and diagonal loading. We show that diagonal loading generally outperforms other alternatives and that Krylov subspace rank reduction can yield a regularization effect close to diagonal loading. Finally, we investigate the impact of preconditioning on the performance and complexity for mismatched modeling and propose a loaded preconditioner, which can reduce complexity as well as preserve the regularization effect. Under the proposed framework, various regularization schemes are studied and some guidelines for choosing the right scheme are provided.