Interference Cancellation at the Relay for Multi-User Wireless Cooperative Networks

We study multi-user transmission and detection schemes for a multi-access relay network (MARN) with linear constraints at all nodes. In a $(J, J_a, R_a, M)$ MARN, $J$ sources, each equipped with $J_a$ antennas, communicate to one $M$-antenna destination through one $R_a$-antenna relay. A new protocol called IC-Relay-TDMA is proposed which takes two phases. During the first phase, symbols of different sources are transmitted concurrently to the relay. At the relay, interference cancellation (IC) techniques, previously proposed for systems with direct transmission, are applied to decouple the information of different sources without decoding. During the second phase, symbols of different sources are forwarded to the destination in a time division multi-access (TDMA) fashion. At the destination, the maximum-likelihood (ML) decoding is performed source-by-source. The protocol of IC-Relay-TDMA requires the number of relay antennas no less than the number of sources, i.e., $R_a\ge J$. Through outage analysis, the achievable diversity gain of the proposed scheme is shown to be $\min\{J_a(R_a-J+1),R_aM\}$. When {\small$M\le J_a\left(1-\frac{J-1}{R_a}\right)$}, the proposed scheme achieves the maximum interference-free (int-free) diversity gain $R_aM$. Since concurrent transmission is allowed during the first phase, compared to full TDMA transmission, the proposed scheme achieves the same diversity, but with a higher symbol rate.Comment: submitted to IEEE Transaction on Wireless Communicatio

MIMO Systems

In recent years, it was realized that the MIMO communication systems seems to be inevitable in accelerated evolution of high data rates applications due to their potential to dramatically increase the spectral efficiency and simultaneously sending individual information to the corresponding users in wireless systems. This book, intends to provide highlights of the current research topics in the field of MIMO system, to offer a snapshot of the recent advances and major issues faced today by the researchers in the MIMO related areas. The book is written by specialists working in universities and research centers all over the world to cover the fundamental principles and main advanced topics on high data rates wireless communications systems over MIMO channels. Moreover, the book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Blind iterative multiuser detection for error coded CDMA systems.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2005.Mobile communications have developed since the radio communications that were in use 50 years ago. With the advent of GSM, mobile communications was brought to the average citizen. More recently, COMA technology has provided the user with higher data rates and more reliable service, and it is apparent that it is the future of wireless communication. With the introduction of 3G technology in South Africa, it is becoming clear that it is the solution to the country's wireless communication requirements. The 3G and next-generation technologies could provide reliable communications to areas where it has proven difficult to operate and maintain communications effectively, such as rural locations. It is therefore important that the se technologies continue to be researched in order to enhance their capabilities to provide a solution to the wireless needs of the local and global community. Whilst COMA is proving to be a reliable communications technology, it is still susceptible to the effects of the near-far problem and multiple-access interference. A number of multiuser detectors have been proposed in literature that attempt to mitigate the effects of multiple-access interference. A notable detector is the blind MOE detector, which requires only the desired user 's spreading sequence , and it exhibits performance approximating that of other linear multiuser detectors. Another promising class of multiuser detector operate using an iterative principle and have a joint multiuser detection and error-correcting coding scheme. The aim of this research is to develop a blind iterative detector with FEC coding as a potential solution to the need for a detector that can mitigate the effects of interfering users operating on the channel. The proposed detector has the benefits of both the blind and iterative schemes: it only requires the knowledge of the desired user ' s signature, and it has integrated error-correcting abilities. The simulation results presented in this dissertation show that the proposed detector exhibits superior performance over the blind MOE detector for various channel conditions. An overview of spread-spectrum technologies is presented, and the operation of OS-COMA is described in more detail. A history and overview of existing COMA standards is also given . The need for multiuser detection is explained, and a description and comparison of various detection methods that have appeared in literature is given. An introduction to error coding is given , with convolutional code s, the turbo coding concept and method s of iterative detection are described in more detail and compared, as iterat ive decoding is fundamental to the operation of an iterative COMA detector. An overview of iterative multiuser detection is given , and selected iterative methods are described in more detail. A blind iterative detector is proposed and analysed. Simulation results for the propo sed detector, and a comparison to the blind MOE detector is presented, showing performance characteristics and the effects of various channel parameters on performance. From these results it can be seen that the proposed detector exhibits a superior performance compared to that of the blind MOE detector for various channel conditions. The dissertation is concluded, and possible future directions of research are given

Interference mitigation using group decoding in multiantenna systems

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Reliable indoor optical wireless communication in the presence of fixed and random blockers

The advanced innovation of smartphones has led to the exponential growth of internet users which is expected to reach 71% of the global population by the end of 2027. This in turn has given rise to the demand for wireless data and internet devices that is capable of providing energy-efficient, reliable data transmission and high-speed wireless data services. Light-fidelity (LiFi), known as one of the optical wireless communication (OWC) technology is envisioned as a promising solution to accommodate these demands. However, the indoor LiFi channel is highly environment-dependent which can be influenced by several crucial factors (e.g., presence of people, furniture, random users' device orientation and the limited field of view (FOV) of optical receivers) which may contribute to the blockage of the line-of-sight (LOS) link. In this thesis, it is investigated whether deep learning (DL) techniques can effectively learn the distinct features of the indoor LiFi environment in order to provide superior performance compared to the conventional channel estimation techniques (e.g., minimum mean square error (MMSE) and least squares (LS)). This performance can be seen particularly when access to real-time channel state information (CSI) is restricted and is achieved with the cost of collecting large and meaningful data to train the DL neural networks and the training time which was conducted offline. Two DL-based schemes are designed for signal detection and resource allocation where it is shown that the proposed methods were able to offer close performance to the optimal conventional schemes and demonstrate substantial gain in terms of bit-error ratio (BER) and throughput especially in a more realistic or complex indoor environment. Performance analysis of LiFi networks under the influence of fixed and random blockers is essential and efficient solutions capable of diminishing the blockage effect is required. In this thesis, a CSI acquisition technique for a reconfigurable intelligent surface (RIS)-aided LiFi network is proposed to significantly reduce the dimension of the decision variables required for RIS beamforming. Furthermore, it is shown that several RIS attributes such as shape, size, height and distribution play important roles in increasing the network performance. Finally, the performance analysis for an RIS-aided realistic indoor LiFi network are presented. The proposed RIS configuration shows outstanding performances in reducing the network outage probability under the effect of blockages, random device orientation, limited receiver's FOV, furniture and user behavior. Establishing a LOS link that achieves uninterrupted wireless connectivity in a realistic indoor environment can be challenging. In this thesis, an analysis of link blockage is presented for an indoor LiFi system considering fixed and random blockers. In particular, novel analytical framework of the coverage probability for a single source and multi-source are derived. Using the proposed analytical framework, link blockages of the indoor LiFi network are carefully investigated and it is shown that the incorporation of multiple sources and RIS can significantly reduce the LOS coverage blockage probability in indoor LiFi systems

Proceedings of the 35th WIC Symposium on Information Theory in the Benelux and the 4th joint WIC/IEEE Symposium on Information Theory and Signal Processing in the Benelux, Eindhoven, the Netherlands May 12-13, 2014

Compressive sensing (CS) as an approach for data acquisition has recently received much attention. In CS, the signal recovery problem from the observed data requires the solution of a sparse vector from an underdetermined system of equations. The underlying sparse signal recovery problem is quite general with many applications and is the focus of this talk. The main emphasis will be on Bayesian approaches for sparse signal recovery. We will examine sparse priors such as the super-Gaussian and student-t priors and appropriate MAP estimation methods. In particular, re-weighted l2 and re-weighted l1 methods developed to solve the optimization problem will be discussed. The talk will also examine a hierarchical Bayesian framework and then study in detail an empirical Bayesian method, the Sparse Bayesian Learning (SBL) method. If time permits, we will also discuss Bayesian methods for sparse recovery problems with structure; Intra-vector correlation in the context of the block sparse model and inter-vector correlation in the context of the multiple measurement vector problem

Channel Coding in Molecular Communication

This dissertation establishes and analyzes a complete molecular transmission system from a communication engineering perspective. Its focus is on diffusion-based molecular communication in an unbounded three-dimensional fluid medium. As a basis for the investigation of transmission algorithms, an equivalent discrete-time channel model (EDTCM) is developed and the characterization of the channel is described by an analytical derivation, a random walk based simulation, a trained artificial neural network (ANN), and a proof of concept testbed setup. The investigated transmission algorithms cover modulation schemes at the transmitter side, as well as channel equalizers and detectors at the receiver side. In addition to the evaluation of state-of-the-art techniques and the introduction of orthogonal frequency-division multiplexing (OFDM), the novel variable concentration shift keying (VCSK) modulation adapted to the diffusion-based transmission channel, the lowcomplex adaptive threshold detector (ATD) working without explicit channel knowledge, the low-complex soft-output piecewise linear detector (PLD), and the optimal a posteriori probability (APP) detector are of particular importance and treated. To improve the error-prone information transmission, block codes, convolutional codes, line codes, spreading codes and spatial codes are investigated. The analysis is carried out under various approaches of normalization and gains or losses compared to the uncoded transmission are highlighted. In addition to state-of-the-art forward error correction (FEC) codes, novel line codes adapted to the error statistics of the diffusion-based channel are proposed. Moreover, the turbo principle is introduced into the field of molecular communication, where extrinsic information is exchanged iteratively between detector and decoder. By means of an extrinsic information transfer (EXIT) chart analysis, the potential of the iterative processing is shown and the communication channel capacity is computed, which represents the theoretical performance limit for the system under investigation. In addition, the construction of an irregular convolutional code (IRCC) using the EXIT chart is presented and its performance capability is demonstrated. For the evaluation of all considered transmission algorithms the bit error rate (BER) performance is chosen. The BER is determined by means of Monte Carlo simulations and for some algorithms by theoretical derivation