Zhigang Yuan

A Novel Nonlinear Companding Transform for PAPR Reduction in Lattice-OFDM System

Abstract In this paper, a novel companding scheme is proposed to reduce the peak-to-average power ratio (PAPR) of lattice orthogonal frequency division multiplexing (LOFDM) system. By transforming the statistics of original signals into a specified distribution form, which is defined by a continuous sine function, this scheme can achieve a simple companding form as well as an improved PAPR and bit-error-rate (BER) performance. Moreover, by introducing the variable companding parameters in the desired probability density function (PDF), a great design flexibility in the companding form and an effective trade-off between the PAPR reduction and BER performance can be achieved to satisfy various system demands. The general formulas of the proposed scheme are derived and a theoretical analysis regarding the achievable transform gain and the selection criteria of companding parameters are also conducted. Simulation results show that the proposed scheme can substantially outperform the conventional μ-law companding, exponential companding (EC), piecewise companding (PC) in terms of PAPR reduction, BER performance and bandwidth efficiency.

Statistic division multiplexing for wireless communication systems

In this paper, wireless statistic division multiplexing (WSDM) is proposed for wireless communication systems, which is a multiplexing scheme that transmits multiple signals simultaneously in the same frequency band over wireless channels. Therefore, the spectrum efficiency of WSDM is high compared to that of time division multiplexing (TDM), frequency division multiplexing (FDM), and code division multiplexing (CDM). WSDM signal is different from TDM, FDM and CDM signal, which is limited in time interval or frequency band or code. The multiple source signals transmitted in WSDM based wireless communication systems are only required to be statistical independent or statistical distinguished. Source signals are recovered at the multiple-antenna receiver by statistical independence or statistical distinction from the received signals. We show theoretically that the information content of all the signal inputs can be recovered by WSDM system. Computer simulation and realistic experimental results validate the performance of our new WSDM system.

A Novel Method for Complex-Valued Signals in Independent Component Analysis Framework

This paper deals with the separation problem of complex-valued signals in the independent component analysis (ICA) framework, where sources are linearly and instantaneously mixed. Inspired by the recently proposed reference-based contrast criteria based on kurtosis, a new contrast function is put forward by introducing the reference-based scheme to negentropy, based on which a novel fast fixed-point (FastICA) algorithm is proposed. This method is similar in spirit to the classical negentropy-based FastICA algorithm, but differs in the fact that it is much more efficient than the latter in terms of computational speed, which is significantly striking with large number of samples. Furthermore, compared with the kurtosis-based FastICA algorithms, this method is more robust against unexpected outliers, which is particularly obvious when the sample size is small. The local consistent property of this new negentropic contrast function is analyzed in detail, together with the derivation of this novel algorithm presented. Performance analysis and comparison are investigated through computer simulations and realistic experiments, for which a simple wireless communication system with two transmitting and receiving antennas is constructed.

New kurtosis optimization algorithms for independent component analysis

This paper considers the independent component analysis (ICA) case in blind source separation (BSS), in which observations result from the linear and instantaneous mixture of sources. Inspired from the recently proposed reference-based contrast criteria, a similar contrast function is proposed, based on which novel optimization algorithms are proposed. They are very similar to the former classical fast fixed-point (FastICA) algorithms based on the kurtosis, but differ in the fact that they are more efficient than the corresponding latter ones respectively in terms of the computational speed, which is particularly striking when the number of samples is large. The validity and performance of the new algorithms are investigated through simulations, in which comparison and analysis are also performed.

Estimation and Cancellation of Nonlinear Companding Noise for Companded Multicarrier Transmission Systems

Nonlinear companding transform (NCT) is an efficient method to reduce the high peak-to-average power ratio (PAPR) of multicarrier transmission systems. However, the introduced companding noise severely restrains the bit-error-rate (BER) performance. In this paper, a general and simple companding noise cancellation (CNC) technique is proposed to mitigate the nonlinear companding noise at the receiver. By exploiting the Bussgang theorem and reconstructing the companding process at the transmitter, the estimated approximate companding noise can be used to refine the received signals. Furthermore, by employing the proposed approach to a typical exponential companding (EC), our results indicate that the proposed scheme can greatly relieve the conventional bottleneck, i.e. the so-called trade-off between the PAPR reduction and BER performance, of NCTs. It shows that for a 512-subcarrier and quadrature phase shift keying modulated orthogonal frequency division multiplexing system, the gap of the signal-to-noise ratio is no more than 0.3 dB at

An improved method for block BSS in time domain by overlapping adjacent blocks

{P_e} = 1 \times {10^{ - 5}}

Cooperation of clipping with companding to improve the BER performance for multicarrier transmission systems with nonlinear HPA

Pe=1×10-5 between the ideal performance bound and EC-CNC regardless of the companding degree (