Adaptive relay techniques for OFDM-based cooperative communication systems

Cooperative communication has been considered as a cost-effective manner to exploit the spatial diversity, improve the quality-of-service and extend transmission coverage. However, there are many challenges faced by cooperative systems which use relays to forward signals to the destination, such as the accumulation of multipath channels, complex resource allocation with the bidirectional asymmetric traffic and reduction of transmission efficiency caused by additional relay overhead. In this thesis, we aim to address the above challenges of cooperative communications, and design the efficient relay systems. Starting with the channel accumulation problem in the amplify-and-forward relay system, we proposed two adaptive schemes for single/multiple-relay networks respectively. These schemes exploit an adaptive guard interval (GI) technique to cover the accumulated delay spread and enhance the transmission efficiency by limiting the overhead. The proposed GI scheme can be implemented without any extra control signal. Extending the adaptive GI scheme to multiple-relay systems, we propose a relay selection strategy which achieves the trade-off between the transmission reliability and overhead by considering both the channel gain and the accumulated delay spread. We then consider resource allocation problem in the two-way decode-and-forward relay system with asymmetric traffic loads. Two allocation algorithms are respectively investigated for time-division and frequency-division relay systems to maximize the end-to-end capacity of the two-way system under a capacity ratio constraint. For the frequency-division systems, a balanced end-to-end capacity is defined as the objective function which combines the requirements of maximizing the end-to-end capacity and achieving the capacity ratio. A suboptimal algorithm is proposed for the frequency-division systems which separates subcarrier allocation and time/power allocation. It can achieve the similar performance with the optimal one with reduced complexity. In order to further enhance the transmission reliability and maintaining low processing delay, we propose an equalize-and-forward (EF) relay scheme. The EF relay equalizes the channel between source and relay to eliminate the channel accumulation without signal regeneration. To reduce the processing time, an efficient parallel structure is applied in the EF relay. Numerical results show that the EF relay exhibits low outage probability at the same data rate as compared to AF and DF schemes

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe

A physiologically inspired model for solving the cocktail party problem.

At a cocktail party, we can broadly monitor the entire acoustic scene to detect important cues (e.g., our names being called, or the fire alarm going off), or selectively listen to a target sound source (e.g., a conversation partner). It has recently been observed that individual neurons in the avian field L (analog to the mammalian auditory cortex) can display broad spatial tuning to single targets and selective tuning to a target embedded in spatially distributed sound mixtures. Here, we describe a model inspired by these experimental observations and apply it to process mixtures of human speech sentences. This processing is realized in the neural spiking domain. It converts binaural acoustic inputs into cortical spike trains using a multi-stage model composed of a cochlear filter-bank, a midbrain spatial-localization network, and a cortical network. The output spike trains of the cortical network are then converted back into an acoustic waveform, using a stimulus reconstruction technique. The intelligibility of the reconstructed output is quantified using an objective measure of speech intelligibility. We apply the algorithm to single and multi-talker speech to demonstrate that the physiologically inspired algorithm is able to achieve intelligible reconstruction of an "attended" target sentence embedded in two other non-attended masker sentences. The algorithm is also robust to masker level and displays performance trends comparable to humans. The ideas from this work may help improve the performance of hearing assistive devices (e.g., hearing aids and cochlear implants), speech-recognition technology, and computational algorithms for processing natural scenes cluttered with spatially distributed acoustic objects.R01 DC000100 - NIDCD NIH HHSPublished versio

Rank-Two Beamforming and Power Allocation in Multicasting Relay Networks

In this paper, we propose a novel single-group multicasting relay beamforming scheme. We assume a source that transmits common messages via multiple amplify-and-forward relays to multiple destinations. To increase the number of degrees of freedom in the beamforming design, the relays process two received signals jointly and transmit the Alamouti space-time block code over two different beams. Furthermore, in contrast to the existing relay multicasting scheme of the literature, we take into account the direct links from the source to the destinations. We aim to maximize the lowest received quality-of-service by choosing the proper relay weights and the ideal distribution of the power resources in the network. To solve the corresponding optimization problem, we propose an iterative algorithm which solves sequences of convex approximations of the original non-convex optimization problem. Simulation results demonstrate significant performance improvements of the proposed methods as compared with the existing relay multicasting scheme of the literature and an algorithm based on the popular semidefinite relaxation technique

Mitigating PAPR in cooperative wireless networks with frequency selective channels and relay selection

The focus of this thesis is peak-to-average power ratio (PAPR) reduction in cooperative wireless networks which exploit orthogonal frequency division multiplexing in transmission. To reduce the PAPR clipping is employed at the source node. The first contribution focuses upon an amplify-and-forward (AF) type network with four relay nodes which exploits distributed closed loop extended orthogonal space frequency block coding to improve end-to-end performance. Oversampling and filtering are used at the source node to reduce out-of-band interference and the iterative amplitude reconstruction decoding technique is used at the destination node to mitigate in-band distortion which is introduced by the clipping process. In addition, by exploiting quantized group feedback and phase rotation at two of the relay nodes, the system achieves full cooperative diversity in addition to array gain. The second contribution area is outage probability analysis in the context of multi-relay selection in a cooperative AF network with frequency selective fading channels. The gains of time domain multi-path fading channels with L paths are modeled with an Erlang distribution. General closed form expressions for the lower and upper bounds of outage probability are derived for arbitrary channel length L as a function of end-to-end signal to noise ratio. This analysis is then extended for the case when single relay selection from an arbitrary number of relay nodes M is performed. The spatial and temporal cooperative diversity gain is then analysed. In addition, exact form of outage probability for multi-path channel length L = 2 and selecting the best single relay from an arbitrary number of relay nodes M is obtained. Moreover, selecting a pair of relays when L = 2 or 3 is additionally analysed. Finally, the third contribution context is outage probability analysis of a cooperative AF network with single and two relay pair selection from M available relay nodes together with clipping at the source node, which is explicitly modelled. MATLAB and Maple software based simulations are employed throughout the thesis to support the analytical results and assess the performance of algorithms and methods

Robust MMSE Precoding Strategy for Multiuser MIMO Relay Systems with Switched Relaying and Side Information

In this work, we propose a minimum mean squared error (MMSE) robust base station (BS) precoding strategy based on switched relaying (SR) processing and limited transmission of side information for interference suppression in the downlink of multiuser multiple-input multiple-output (MIMO) relay systems. The BS and the MIMO relay station (RS) are both equipped with a codebook of interleaving matrices. For a given channel state information (CSI) the selection function at the BS chooses the optimum interleaving matrix from the codebook based on two optimization criteria to design the robust precoder. Prior to the payload transmission the BS sends the index corresponding to the selected interleaving matrix to the RS, where the best interleaving matrix is selected to build the optimum relay processing matrix. The entries of the codebook are randomly generated unitary matrices. Simulation results show that the performance of the proposed techniques is significantly better than prior art in the case of imperfect CSI.