On Information and Energy Cooperation in Energy Harvesting Cognitive Radio

This paper considers the cooperation between primary and secondary users at information and energy levels when both users are energy harvesting nodes. In particular, a secondary transmitter helps relaying the primary message, and in turn, gains the spectrum access as a reward. Also, the primary transmitter supplies energy to the secondary transmitter if the latter is energy-constrained, which facilitates an uninterrupted cooperation. We address this two-level cooperation over a finite horizon with the finite battery constraint at the secondary transmitter. While promising the rate-guaranteed service to both primary and secondary users, we aim to maximize the primary rate. We develop an iterative algorithm that obtains the optimal offline power policies for primary and secondary users. To acquire insights about the structure of the optimal solution, we examine specific scenarios. Furthermore, we investigate the effects of the secondary rate constraint and finite battery on the primary rate and the probability of cooperation. We show that the joint information and energy cooperation increases the chances of cooperation and achieves significant rate gains over only information cooperation.Comment: 6 pages, 4 figures, to be presented in IEEE PIMRC 201

Performance Analysis of Cooperative Hybrid Cognitive Radio Network with Various Diversity Techniques

The extensive growth in wireless communications leads to spectrum scarcity. Since the spectrum is limited spectrum usage is clogged. The best possible solution is usage of cognitive radio. A cognitive radio network with sender, receiver and intermediate devices as relays is analyzed. The channel is modelled with noise considerations, path loss and variance. The system is defined with one primary sender and one primary receiver, in between them five secondary users and two active users. The signals from all these paths are estimated and analyzed to draw the best signal with good signal to noise ratio (SNR). To improve the channel efficiency and quality, we have considered various diversity techniques for which the fading problem of channel can be eliminated. In view of this, we concentrated on improving the system performance with various diversity techniques and optimum weight adaptation concept

Dynamic Spectrum Sharing in Cognitive Radio and Device-to-Device Systems

abstract: Cognitive radio (CR) and device-to-device (D2D) systems are two promising dynamic spectrum access schemes in wireless communication systems to provide improved quality-of-service, and efficient spectrum utilization. This dissertation shows that both CR and D2D systems benefit from properly designed cooperation scheme. In underlay CR systems, where secondary users (SUs) transmit simultaneously with primary users (PUs), reliable communication is by all means guaranteed for PUs, which likely deteriorates SUs’ performance. To overcome this issue, cooperation exclusively among SUs is achieved through multi-user diversity (MUD), where each SU is subject to an instantaneous interference constraint at the primary receiver. Therefore, the active number of SUs satisfying this constraint is random. Under different user distributions with the same mean number of SUs, the stochastic ordering of SU performance metrics including bit error rate (BER), outage probability, and ergodic capacity are made possible even without observing closed form expressions. Furthermore, a cooperation is assumed between primary and secondary networks, where those SUs exceeding the interference constraint facilitate PU’s transmission by relaying its signal. A fundamental performance trade-off between primary and secondary networks is observed, and it is illustrated that the proposed scheme outperforms non-cooperative underlay CR systems in the sense of system overall BER and sum achievable rate. Similar to conventional cellular networks, CR systems suffer from an overloaded receiver having to manage signals from a large number of users. To address this issue, D2D communications has been proposed, where direct transmission links are established between users in close proximity to offload the system traffic. Several new cooperative spectrum access policies are proposed allowing coexistence of multiple D2D pairs in order to improve the spectral efficiency. Despite the additional interference, it is shown that both the cellular user’s (CU) and the individual D2D user's achievable rates can be improved simultaneously when the number of D2D pairs is below a certain threshold, resulting in a significant multiplexing gain in the sense of D2D sum rate. This threshold is quantified for different policies using second order approximations for the average achievable rates for both the CU and the individual D2D user.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Energy efficient planning and operation models for wireless cellular networks

Prospective demands of next-generation wireless networks are ambitious and will require cellular networks to support 1000 times higher data rates and 10 times lower round-trip latency. While this data deluge is a natural outcome of the increasing number of mobile devices with data hungry applications and the internet of things (IoT), the low latency demand is required by the future interactive applications such as tactile internet , virtual and enhanced reality, and online internet gaming, etc. The motivation behind this thesis is to meet the increasing quality of service (QoS) demands in wireless communications and reduce the global carbon footprint at the same time. To achieve these goals, energy efficient planning and operations models for wireless cellular networks are proposed and analyzed. Firstly, a solution based on the overlay cognitive radio (CR) along with cooperative relaying is proposed to reduce the effect of the scarcity problem of the radio spectrum. In overlay technique, the primary users (PUs) cooperate with cognitive users (CUs) for mutual benefits. The achievable cognitive rate of two-way relaying (TWR) system assisted by multiple antennas is proposed. Compared to traditional relaying where the transmission to exchange two different messages between two sources takes place in four time slots, using TWR, the required number of transmission slots reduces to two slots. In the first slot, both sources transmit their signals simultaneously to the relay. Then, during the second slot the relay broadcasts its signal to the sources. Using an overlay CR technique, the CUs are allowed to allocate part of the PUs\u27 spectrum to perform their cognitive transmission. In return, acting as amplify-and-forward (AF) TWR, the CUs are exploited to support PUs to reach their target data rates over the remaining bandwidth. A meta-heuristic approach based on particle swarm optimization algorithm is proposed to find a near optimal resource allocation in addition to the relay amplification matrix gains. Then, we investigate a multiple relay selection scheme for energy harvesting (EH)-based on TWR system. All the relays are considered as EH nodes that harvest energy from renewable and radio frequency sources, where the relays forward the information to the sources. The power-splitting protocol, in which the receiver splits the input radio frequency signal into two components: one for information transmission and the other for energy harvesting, is adopted at the relay side. An approximate optimization framework based on geometric programming is established in a convex form to find near optimal PS ratios, the relays’ transmission power, and the selected relays in order to maximize the total rate utility over multiple time slots. Different utility metrics are considered and analyzed depending on the level of fairness. Secondly, a downlink resource and energy management approach for heterogeneous networks (HetNets) is proposed, where all base stations (BSs) are equipped to harvest energy from renewable energy (RE) sources. A hybrid power supply of green (renewable) and traditional micro-grid, such that the traditional micro-grid is not exploited as long as the BSs can meet their power demands from harvested and stored green energy. Furthermore, a dynamic BS switching ON/OFF combined with the EH model, where some BSs are turned off due to the low traffic periods and their stored energy in order to harvest more energy and help efficiently during the high traffic periods. A binary linear programming (BLP) optimization problem is formulated and solved optimally to minimize the network-wide energy consumption subject to users\u27 certain quality of service and BSs\u27 power consumption constraints. Moreover, green communication algorithms are implemented to solve the problem with low complexity time. Lastly, an energy management framework for cellular HetNets supported by dynamic drone small cells is proposed. A three-tier HetNet composed of a macrocell BS, micro cell BSs (MBSs), and solar powered drone small cell BSs are deployed to serve the networks\u27 subscribers. In addition to the RE, the drones can power their batteries via a charging station located at the macrocell BS site. Pre-planned locations are identified by the mobile operator for possible drones\u27 placement. The objective of this framework is to jointly determine the optimal locations of the drones in addition to the MBSs that can be safely turned off in order to minimize the daily energy consumption of the network. The framework takes also into account the cells\u27 capacities and the QoS level defined by the minimum required receiving power. A BLP problem is formulated to optimally determine the network status during a time-slotted horizon