A binary direct-sequence spread-spectrum multiple-access system with random sequences in flat Rayleigh fading is considered. A new explicit closed-form expression is obtained for the characteristic function of the multiple-access interference signals. It is shown that the overall error rate can be expressed by a single integral whose integrand is nonnegative and exponentially decaying. Bit-error rates (BERs) are obtained with this expression to any desired accuracy with minimal computational complexity. The dependence of the system BER on the number of transitions in the target user signature chip sequence is explicitly derived. The results are used to examine definitively the validity of three Gaussian approximations and to compare the performances of synchronous systems to asynchronous systems.

Accurate DS-CDMA bit-error probability calculation in Rayleigh fading

Bit error probability approximation for short-time Fourier transform based nonstationary interference excision in DS-SS systems

(08/12/2018)  RF subsystem power consumption and induced radiation emulation The thesis introduces a novel approach towards the emulation of the RF subsystem power consumption when transmitting a LTE signal. The RF subsystem which is made up of analog components has not been covered by the status quo emulation methodologies which are compatible with digital circuits. Though the study of the RF subsystem architectures revealed numerous architectures with different impacts on power consumption, we have decided to consider the RF subsystem as a black box.

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RF subsystem power consumption and induced radiation emulation

A major limiting factor in the performance of multiple-input-multiple-output (MIMO) code division multiple access (CDMA) systems is multiple access interference (MAI) which can reduce the system’s capacity and increase its bit error rate (BER). Thus, a statistical characterization of the MAI is vital in analyzing the performance of such systems. Since the statistical analysis of MAI in MIMO-CDMA systems is quite involved, especially when these systems are fading, existing works in the literature, such as successive interference cancellation (SIC) or parallel interference cancellation (PIC), employ suboptimal approaches to detect the subscriber without involving the need for MAI statistics. The knowledge of both MAI and noise statistics plays a vital role in various applications such as the design of an optimum receiver based on maximum likelihood (ML) detection, evaluation of the probability of bit error, calculation of the system’s capacity, evaluation of the outage probability, estimation of the channel’s impulse response using methods including the minimum mean-square-error (MMSE), the maximum likelihood(ML), and the maximum a posteriori probability (MAP) criterion. To the best of our knowledge, there is no existing work that explicitly evaluates the statistics of the MAI-plus-noise in MIMO fading channels. This constitutes the prime objective of our proposed study here. In this work, we derive the expressions for the probability density function (PDF) of MAI and MAI-plus-noise in MIMO-CDMA systems in the presence of both Rayleigh fading channels and additive white Gaussian noise. Moreover, we evaluate the probability of the bit error rate in the presence of optimum reception using a ML receiver. Our theoretical findings can provide a reliable basis for both system design and various performance analyses of such systems. Our simulation results show that the theoretical findings are very well substantiated.

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Multiple access interference in MIMO-CDMA systems under Rayleigh fading: statistical characterization and applications

Researchers have shown that by combining multiple input multiple output (MIMO) techniques with CDMA then higher gains in capacity, reliability and data transmission speed can be attained. But a major drawback of MIMO-CDMA systems is multiple access interference (MAI) which can reduce the capacity and increase the bit error rate (BER), so statistical analysis of MAI becomes a very important factor in the performance analysis of these systems. In this thesis, a detailed analysis of MAI is performed for binary phase-shift keying (BPSK) signals with random signature sequence in Raleigh fading environment and closed from expressions for the probability density function of MAI and MAI with noise are derived. Further, probability of error is derived for the maximum Likelihood receiver. These derivations are veri ed through simulations and are found to reinforce the theoretical results. Since the performance of MIMO su ers signi cantly from MAI and inter-symbol interference (ISI), equalization is needed to mitigate these e ects. It is well known from the theory of constrained optimization that the learning speed of any adaptive ltering algorithm can be increased by adding a constraint to it, as in the case of the normalized least mean squared (NLMS) algorithm. Thus, in this work both linear and non-linear decision feedback (DFE) equalizers for MIMO systems with least mean square (LMS) based constrained stochastic gradient algorithm have been designed. More speci cally, an LMS algorithm has been developed , which was equipped with the knowledge of number of users, spreading sequence (SS) length, additive noise variance as well as MAI with noise (new constraint) and is named MIMO-CDMA MAI with noise constrained (MNCLMS) algorithm. Convergence and tracking analysis of the proposed algorithm are carried out in the scenario of interference and noise limited systems, and simulation results are presented to com-

/pdf/constrained-linear-and-non-linear-adaptive-equalization-53jpfnhr4o.pdf

Constrained Linear and Non-Linear Adaptive Equalization Techniques for MIMO-CDMA Systems

Many papers have described the calculation of error probabilities for a direct-sequence/spread-spectrum multiple-access system. The exact calculation is computationally difficult, so emphasis has been placed on the approximation and the bounds. A simple and attractive approximation is the Gaussian approximation in which the signal/noise ratio is used. Unfortunately, this approximation is not accurate enough in some cases. The authors present a method for improving the Gaussian approximation accuracy. The authors use a number of moments of multiple-access interference (MAI) to make the approximation more accurate.

J.D. Hu

Papers

Method to improve Gaussian approximation accuracy for calculation of spread-spectrum multiple-access error probabilities