Problem Of Receiver Design Research Articles

Robust receiver for OFDM-DCSK modulation via rank-1 modeling and [formula omitted]-minimization

In this paper, the problem of receiver design for orthogonal frequency division multiplexing differential chaos shift keying (OFDM-DCSK) communication systems is addressed. By exploiting the rank-1 property of the symbol matrix, we propose to apply dimensionality reduction on the time-domain data symbols received from the OFDM-DCSK transmitter for noise reduction, followed by chaotic demodulation on the resultant symbols to decode the information bits. In the presence of additive white Gaussian noise (AWGN), the rank-1 matrix approximation can be simply achieved by the truncated singular value decomposition, corresponding to the solution of ℓ2-norm minimization. While for impulsive noise environments such as in power line communication systems, we develop an alternating optimization algorithm for ℓp-based matrix factorization, where 0<p<2. The bit error rate (BER) of our approach in AWGN is also analyzed and verified. Simulation results demonstrate that the devised receiver is superior to the conventional OFDM-DCSK method in terms of BER and root mean square error performance for AWGN as well as impulsive noise including the Middleton class A distribution and α-stable process.

A Distributionally Robust Linear Receiver Design for Multi-Access Space-Time Block Coded MIMO Systems

A receiver design problem for multi-access space-time block coded multiple-input multiple-output systems is considered. To hedge the mismatch between the true and the estimated channel state information (CSI), several robust receivers have been developed in the past decades. Among these receivers, the Gaussian robust receiver has been shown to be superior in performance. This receiver is designed based on the assumption that the CSI mismatch has Gaussian distribution. However, in real-world applications, the assumption of Guassianity might not hold. Motivated by this fact, a more general distributionally robust receiver is proposed in this paper, where only the mean and the variance of the CSI mismatch distribution are required in the receiver design. A tractable semi-definite programming (SDP) reformulation of the robust receiver design is developed. To suppress the self-interferences, a more advanced distributionally robust receiver is proposed. A tight convex approximation is given and the corresponding tractable SDP reformulation is developed. Moreover, for the sake of easy implementation, we present a simplified distributionally robust receiver. Simulations results are provided to show the effectiveness of our design by comparing with some existing well-known receivers.

A DETECTION TECHNIQUE OF SIGNAL IN MIMO SYSTEM

MIMO techniques are based on multiple antennae in receiving and transmitting signals and also used in multipath propagation for the transformation of entire channel into many independent virtual channels. In MIMO system multiple antennae can increase the spectral efficiency/ reliability of radio channel without increasing bandwidth or transmit power. Commercially, it is not feasible in case of MIMO systems. So, simple and efficient receiver that can harness MIMO architecture benefits without draining mobile receiver battery power or long time to decode transmitted symbols was required. In this paper problem of receiver design for MIMO system in spatial multiplexing scheme that is Maximum likelihood detection problem also known as NP hard combinatorial optimization problem, which need an exponential search over the space of all possible transmitted symbols in order to find closest point in Euclidean sense to received symbols, has been considered. A metaheuristic algorithm for detection of MIMO wireless system based on the Ant colony optimization (ACO) technique using MATLAB give the best solution to the problem and find the optimal path for the receivers.

Minimum SER Block Precoding and Equalization for Frequency-Selective Fading Channels

In this paper, we study the joint transmitter and receiver design problem over frequency-selective fading channels. Motivated by a conventional minimum mean square error decision feedback equalizer (MMSE-DFE), we present a simple approximate maximum-likelihood (ML) decision feedback equalizer at the receiver. We then perform precoding in a downlink scenario at the transmitter side to minimize the analytical symbol error rate (SER) of the proposed equalization scheme. Simulation results indicate that the proposed precoder achieves substantial performance gains over previously reported techniques.

Statistical Precoding With Decision Feedback Equalization Over a Correlated MIMO Channel

The decision feedback (DF) transceiver, combining linear precoding and DF equalization, can establish point-to-point communication over a wireless multiple-input multiple-output channel. Matching the DF-transceiver design parameters to the channel characteristics can improve system performance, but requires channel knowledge. We consider the fast-fading channel scenario, with a receiver capable of tracking the channel-state variations accurately, while the transmitter only has long-term, channel-distribution information. The receiver design problem given channel-state information is well studied in the literature. We focus on transmitter optimization, which amounts to designing a statistical precoder to assist the channel-tailored DF equalizer. We develop a design framework that encompasses a wide range of performance metrics. Common cost functions for precoder optimization are analyzed, thereby identifying a structure of typical cost functions. Transmitter design is approached for typical cost functions in general, and we derive a precoder design formulation as a convex optimization problem. Two important subclasses of cost functions are considered in more detail. First, we explore a symmetry of DF transceivers with a uniform subchannel rate allocation, and derive a simplified convex optimization problem, which can be efficiently solved even as system dimensions grow. Second, we explore the tractability of a certain class of mean square error based cost functions, and solve the transmitter design problem with a simple algorithm that identifies the convex hull of a set of points in R2. The behavior of DF transceivers with optimal precoders is investigated by numerical means.

Receiver Design for Uplink Multiuser Code Division Multiple Access Communication System Based on Neural Network

In this paper, we consider the receiver design problem for the uplink multiuser code division multiple access (CDMA) communication system based on the neural network technique. The uplink multiuser CDMA communication system model is described in the form of space---time domain through antenna array and multipath fading expression. Novel suitable neural network technique is proposed as an effective signal processing method for the receiver of such an uplink multiuser CDMA system. By the appropriate choice of the channel state information for the neural network parameters, the neural network can collectively resolve the effects of both the inter-symbol interference due to the multipath fading channel and the multiple access interference in the receiver of the uplink multiuser CDMA communication system. The dynamics of the proposed neural network receiver for the uplink multiuser CDMA communication system is also studied.

Approximate maximum likelihood serial decision-feedback equaliser and Tomlinson–Harashima pre-equalisation

Joint transmitter and receiver design problem for frequency-selective, time-invariant fading channels are studied. The authors first propose a simple approximate maximum likelihood serial decision-feedback equaliser (A-ML-SDFE) through DFE, a Gaussian approximation, a pre-whitening filter and a matched filter. Secondly, assuming full channel knowledge available at the transmitter side, the authors perform pre-equalisation in a downlink scenario by moving the decision-feedback part of the A-ML-SDFE to the transmitter. The proposed A-ML-SDFE achieves much better performance than linear minimum mean square error (MMSE) and MMSE-DFE with a lower complexity. The pre-equaliser further improves the system performance at low signal-to-noise ratio with a reduced receiver complexity.