Cooperation and Underlay Mode Selection in Cognitive Radio Network

In this research, we proposes a new method for cooperation and underlay mode selection in cognitive radio networks. We characterize the maximum achievable throughput of our proposed method of hybrid spectrum sharing. Hybrid spectrum sharing is assumed where the Secondary User (SU) can access the Primary User (PU) channel in two modes, underlay mode or cooperative mode with admission control. In addition to access the channel in the overlay mode, secondary user is allowed to occupy the channel currently occupied by the primary user but with small transmission power. Adding the underlay access modes attains more opportunities to the secondary user to transmit data. It is proposed that the secondary user can only exploits the underlay access when the channel of the primary user direct link is good or predicted to be in non-outage state. Therefore, the secondary user could switch between underlay spectrum sharing and cooperation with the primary user. Hybrid access is regulated through monitoring the state of the primary link. By observing the simulation results, the proposed model attains noticeable improvement in the system performance in terms of maximum secondary user throughput than the conventional cooperation and non-cooperation schemes

Distributed Game Theoretic Optimization and Management of Multichannel ALOHA Networks

The problem of distributed rate maximization in multi-channel ALOHA networks is considered. First, we study the problem of constrained distributed rate maximization, where user rates are subject to total transmission probability constraints. We propose a best-response algorithm, where each user updates its strategy to increase its rate according to the channel state information and the current channel utilization. We prove the convergence of the algorithm to a Nash equilibrium in both homogeneous and heterogeneous networks using the theory of potential games. The performance of the best-response dynamic is analyzed and compared to a simple transmission scheme, where users transmit over the channel with the highest collision-free utility. Then, we consider the case where users are not restricted by transmission probability constraints. Distributed rate maximization under uncertainty is considered to achieve both efficiency and fairness among users. We propose a distributed scheme where users adjust their transmission probability to maximize their rates according to the current network state, while maintaining the desired load on the channels. We show that our approach plays an important role in achieving the Nash bargaining solution among users. Sequential and parallel algorithms are proposed to achieve the target solution in a distributed manner. The efficiencies of the algorithms are demonstrated through both theoretical and simulation results.Comment: 34 pages, 6 figures, accepted for publication in the IEEE/ACM Transactions on Networking, part of this work was presented at IEEE CAMSAP 201

Chernoff bounds on pairwise error probabilities of space-time codes

We derive Chernoff bounds on pairwise error probabilities of coherent and noncoherent space-time signaling schemes. First, general Chernoff bound expressions are derived for a correlated Ricean fading channel and correlated additive Gaussian noise. Then, we specialize the obtained results to the cases of space-time-separable noise, white noise, and uncorrelated fading. We derive approximate Chernoff bounds for high and low signal-to-noise ratios (SNRs) and propose optimal signaling schemes. We also compute the optimal number of transmitter antennas for noncoherent signaling with unitary mutually orthogonal space-time codes

How Equalization Techniques Affect the TCP Performance of MC-CDMA Systems in Correlated Fading Channels

This paper investigates the impact of several equalization techniques for multicarrier code division multiple access systems on the performance at both lower and upper layers (i.e., physical and TCP layers). Classical techniques such as maximal ratio combining, equal gain combining, orthogonality restoring combining, minimum mean square error, as well as a partial equalization (PE) are investigated in time- and frequency-correlated fading channels with various numbers of interferers. Their impact on the performance at upper level is then studied. The results are obtained through an integrated simulation platform carefully reproducing all main aspects affecting the quality of service perceived by the final user, allowing an investigation of the real gain produced by signal processing techniques at TCP level

Maximizing signal to leakage ratios in MIMO BCH cooperative beamforming scheme

Beamforming (BF) technique in cooperative multiple input multiple output (MIMO) antenna arrays improves signal to noise ratio (SNR) of the intended user. The challenge is to design transmit beamforming vectors for every user while limiting the co-channel interference (CCI) from other users. In this paper, we proposed cooperative beamforming based on Signal-to-Leakage Ratio (SLR) to exploit the leakage power as a useful power in the second time slot after user cooperation, for this purpose successive interference cancellation (SIC) is employed in each user to separate the leakage signal from the desired signal. Without increasing the complexity, Maximizing Signal-to-Leakage Ratio (SLR) subject to proposed power constraint instead of a unity norm is the way to achieve extra leakage power. To reduce the erroneous, Bose–Chaudhuri–Hocquenghem (BCH) codes employed in Beamforming of (SIC) cooperative scheme BF(CS-SIC-BCH). Maximum-likelihood (ML) estimator method is used at each user receiver. Simulation results show that the performance of the proposed scheme BF (CS-SIC-BCH) over Rayleigh and Rician fading channel is significantly better than the performance beamforming based on SLR in Non-cooperative system. More specifically to achieve a BER of about the required SNR for the proposed scheme is about 1 dB less than the Non-cooperative system

Finite Random Matrix Theory Analysis of Multiple Antenna Communication Systems

Multiple-antenna systems are capable of providing substantial improvement to wireless communication networks, in terms of data rate and reliability. Without utilizing extra spectrum or power resources, multiple-antenna technology has already been supported in several wireless communication standards, such as LTE, WiFi and WiMax. The surging popularity and enormous prospect of multiple-antenna technology require a better understanding to its fundamental performance over practical environments. Motivated by this, this thesis provides analytical characterizations of several seminal performance measures in advanced multiple-antenna systems. The analytical derivations are mainly based on finite dimension random matrix theory and a collection of novel random matrix theory results are derived. The closed-form probability density function of the output of multiple-input multiple-output (MIMO) block-fading channels is studied. In contrast to the existing results, the proposed expressions are very general, applying for arbitrary number of antennas, arbitrary signal-to-noise ratio and multiple classical fading models. Results are presented assuming two input structures in the system: the independent identical distributed (i.i.d.) Gaussian input and a product form input. When the channel is fed by the i.i.d. Gaussian input, analysis is focused on the channel matrices whose Gramian is unitarily invariant. When the channel is fed by a product form input, analysis is conducted with respect to two capacity-achieving input structures that are dependent upon the relationship between the coherence length and the number of antennas. The mutual information of the systems can be computed numerically from the pdf expression of the output. The computation is relatively easy to handle, avoiding the need of the straight Monte-Carlo computation which is not feasible in large-dimensional networks. The analytical characterization of the output pdf of a single-user MIMO block-fading channels with imperfect channel state information at the receiver is provided. The analysis is carried out under the assumption of a product structure for the input. The model can be thought of as a perturbation of the case where the statistics of the channel are perfectly known. Specifically, the average singular values of the channel are given, while the channel singular vectors are assumed to be isotropically distributed on the unitary groups of dimensions given by the number of transmit and receive antennas. The channel estimate is affected by a Gaussian distributed error, which is modeled as a matrix with i.i.d. Gaussian entries of known covariance. The ergodic capacity of an amplify-and-forward (AF) MIMO relay network over asymmetric channels is investigated. In particular, the source-relay and relay-destination channels undergo Rayleigh and Rician fading, respectively. Considering arbitrary-rank means for the relay-destination channel, the marginal distribution of an unordered eigenvalue of the cascaded AF channel is presented, thus the analytical expression of the ergodic capacity of the system is obtained. The results indicate the impact of the signal-to-noise ratio and of the Line-of-Sight component on such asymmetric relay network