Throughput Maximization of Cognitive Radio Multi Relay Network with Interference Management

In this paper, an Orthogonal Frequency Division Multiplexing (OFDM) based cognitive multi relay network is investigated to maximize the transmission rate of the cognitive radio (CR) with enhanced  fairness among CR users  with interference to the primary users (PUs) being managed below a certain threshold level. In order to improve the transmission rate of the CR, optimization of the subcarrier pairing and power allocation is to be carried out simultaneously. Firstly joint optimization problem is formulated and Composite Genetic and Ordered Subcarrier Pairing (CGOSP) algorithm is proposed to solve the problem. The motivation behind merging genetic and OSP algorithm is to reduce the complexity of Genetic Algorithm (GA). Further, to have a fair allocation of resources among CR users, the Round Robin allocation method is adopted so as to allocate subcarrier pairs to relays efficiently. The degree of fairness of the system is calculated using Jain’s Fairness Index (JFI). Simulation results demonstrate the significant improvement in transmission rate of the CR, low computational complexity and enhanced fairness

Modified quasi-orthogonal space-time block coding in distributed wireless networks

Cooperative networks have developed as a useful technique that can achieve the same advantage as multi-input and multi-output (MIMO) wireless systems such as spatial diversity, whilst resolving the difficulties of co-located multiple antennas at individual nodes and avoiding the effect of path-loss and shadowing. Spatial diversity in cooperative networks is known as cooperative diversity, and can enhance system reliability without sacrificing the scarce bandwidth resource or consuming more transmit power. It enables single-antenna terminals in a wireless relay network to share their antennas to form a virtual antenna array on the basis of their distributed locations. However, there remain technical challenges to maximize the benefit of cooperative communications, e.g. data rate, asynchronous transmission and outage. In this thesis, therefore, firstly, a modified distributed quasi-orthogonal space-time block coding (M-D-QO-STBC) scheme with increased code gain distance (CGD) for one-way and two-way amplify-and-forward wireless relay networks is proposed. This modified code is designed from set partitioning a larger codebook formed from two quasi-orthogonal space time block codes with different signal rotations then the subcodes are combined and pruned to arrive at the modified codebook with the desired rate in order to increase the CGD. Moreover, for higher rate codes the code distance is maximized by using a genetic algorithm to search for the optimum rotation matrix. This scheme has very good performance and significant coding gain over existing codes such as the open-loop and closed-loop QO-STBC schemes. In addition, the topic of outage probability analysis in the context of multi-relay selection from $N$ available relay nodes for one-way amplify-and-forward cooperative relay networks is considered together with the best relay selection, the $N^{th}$ relay selection and best four relay selection in two-way amplify-and-forward cooperative relay networks. The relay selection is performed either on the basis of a max-min strategy or one based on maximizing exact end-to-end signal-to-noise ratio. Furthermore, in this thesis, robust schemes for cooperative relays based on the M-D-QO-STBC scheme for both one-way and two-way asynchronous cooperative relay networks are considered to overcome the issue of a synchronism in wireless cooperative relay networks. In particular, an orthogonal frequency division multiplexing (OFDM) data structure is employed with cyclic prefix (CP) insertion at the source in the one-way cooperative relay network and at the two terminal nodes in the two-way cooperative network to combat the effects of time asynchronism. As such, this technique can effectively cope with the effects of timing errors. Finally, outage probability performance of a proposed amplify-and-forward cooperative cognitive relay network is evaluated and the cognitive relays are assumed to exploit an overlay approach. A closed form expression for the outage probability for multi-relay selection cooperation over Rayleigh frequency flat fading channels is derived for perfect and imperfect spectrum acquisitions. Furthermore, the M-QO-STBC scheme is also proposed for use in wireless cognitive relay networks. MATLAB and Maple software based simulations are employed throughout the thesis to support the analytical results and assess the performance of new algorithms and methods

Distributed Adaptation Techniques for Connected Vehicles

In this PhD dissertation, we propose distributed adaptation mechanisms for connected vehicles to deal with the connectivity challenges. To understand the system behavior of the solutions for connected vehicles, we first need to characterize the operational environment. Therefore, we devised a large scale fading model for various link types, including point-to-point vehicular communications and multi-hop connected vehicles. We explored two small scale fading models to define the characteristics of multi-hop connected vehicles. Taking our research into multi-hop connected vehicles one step further, we propose selective information relaying to avoid message congestion due to redundant messages received by the relay vehicle. Results show that the proposed mechanism reduces messaging load by up to 75% without sacrificing environmental awareness. Once we define the channel characteristics, we propose a distributed congestion control algorithm to solve the messaging overhead on the channels as the next research interest of this dissertation. We propose a combined transmit power and message rate adaptation for connected vehicles. The proposed algorithm increases the environmental awareness and achieves the application requirements by considering highly dynamic network characteristics. Both power and rate adaptation mechanisms are performed jointly to avoid one result affecting the other negatively. Results prove that the proposed algorithm can increase awareness by 20% while keeping the channel load and interference at almost the same level as well as improve the average message rate by 18%. As the last step of this dissertation, distributed cooperative dynamic spectrum access technique is proposed to solve the channel overhead and the limited resources issues. The adaptive energy detection threshold, which is used to decide whether the channel is busy, is optimized in this work by using a computationally efficient numerical approach. Each vehicle evaluates the available channels by voting on the information received from one-hop neighbors. An interdisciplinary approach referred to as entropy-based weighting is used for defining the neighbor credibility. Once the vehicle accesses the channel, we propose a decision mechanism for channel switching that is inspired by the optimal flower selection process employed by bumblebees foraging. Experimental results show that by using the proposed distributed cooperative spectrum sensing mechanism, spectrum detection error converges to zero

Recent advances in radio resource management for heterogeneous LTE/LTE-A networks

As heterogeneous networks (HetNets) emerge as one of the most promising developments toward realizing the target specifications of Long Term Evolution (LTE) and LTE-Advanced (LTE-A) networks, radio resource management (RRM) research for such networks has, in recent times, been intensively pursued. Clearly, recent research mainly concentrates on the aspect of interference mitigation. Other RRM aspects, such as radio resource utilization, fairness, complexity, and QoS, have not been given much attention. In this paper, we aim to provide an overview of the key challenges arising from HetNets and highlight their importance. Subsequently, we present a comprehensive survey of the RRM schemes that have been studied in recent years for LTE/LTE-A HetNets, with a particular focus on those for femtocells and relay nodes. Furthermore, we classify these RRM schemes according to their underlying approaches. In addition, these RRM schemes are qualitatively analyzed and compared to each other. We also identify a number of potential research directions for future RRM development. Finally, we discuss the lack of current RRM research and the importance of multi-objective RRM studies

Location Aided Energy Balancing Strategy in Green Cellular Networks

Most cellular network communication strategies are focused on data traffic scenarios rather than energy balance and efficient utilization. Thus mobile users in hot cells may suffer from low throughput due to energy loading imbalance problem. In state of art cellular network technologies, relay stations extend cell coverage and enhance signal strength for mobile users. However, busy traffic makes the relay stations in hot area run out of energy quickly. In this paper, we propose an energy balancing strategy in which the mobile nodes are able to dynamically select and hand over to the relay station with the highest potential energy capacity to resume communication. Key to the strategy is that each relay station merely maintains two parameters that contains the trend of its previous energy consumption and then predicts its future quantity of energy, which is defined as the relay station potential energy capacity. Then each mobile node can select the relay station with the highest potential energy capacity. Simulations demonstrate that our approach significantly increase the aggregate throughput and the average life time of relay stations in cellular network environment.Comment: 6 pages, 5 figures. arXiv admin note: text overlap with arXiv:1108.5493 by other author

Secondary Network Throughput Optimization of NOMA Cognitive Radio Networks Under Power and Secure Constraints

Recently, the combination of cognitive radio networks with the nonorthogonal multiple access (NOMA) approach has emerged as a viable option for not only improving spectrum usage but also supporting large numbers of wireless communication connections. However, cognitive NOMA networks are unstable and vulnerable because multiple devices operate on the same frequency band. To overcome this drawback, many techniques have been proposed, such as optimal power allocation and interference cancellation. In this paper, we consider an approach by which the secondary transmitter (STx) is able to find the best licensed channel to send its confidential message to the secondary receivers (SRxs) by using the NOMA technique. To combat eavesdroppers and achieve reasonable performance, a power allocation policy that satisfies both the outage probability (OP) constraint of primary users and the security constraint of secondary users is optimized. The closed-form formulas for the OP at the primary base station and the leakage probability for the eavesdropper are obtained with imperfect channel state information. Furthermore, the throughput of the secondary network is analyzed to evaluate the system performance. Based on that, two algorithms (i.e., the continuous genetic algorithm (CGA) for CR NOMA (CGA-CRN) and particle swarm optimization (PSO) for CR NOMA (PSO-CRN)), are applied to optimize the throughput of the secondary network. These optimization algorithms guarantee not only the performance of the primary users but also the security constraints of the secondary users. Finally, simulations are presented to validate our research results and provide insights into how various factors affect system performance