Resource Allocation in Wireless Networks for Secure Transmission and Utility Maximization
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Resource allocation in wireless networks is one of the most studied class of problems. Generally, these problems are formulated as utility maximization problems under relevant constraints. The challenges posed by these problems vary widely depending on the nature of the utility function under consideration. Recently, the widespread prevalence of wireless devices prompted researchers and engineers to delve into the security issues of wireless communication. As compared to the wired medium, ensuring security for the wireless medium is more challenging mainly due to the broadcast nature of the transmission. But the ongoing research on physical layer security promises robust and reliable security schemes for wireless communication. Contrary to conventional cryptographic schemes, physical layer security techniques are impregnable as the security is ensured by the inherent randomness present in the wireless medium. In this thesis, we consider several wireless scenarios and propose secrecy enhancing resource allocation schemes for them in the first few chapters. We initially address the problem of secure transmission by following the conventional approach in the secrecy literature|secrecy rate maximization. Needless to say, in these chapters, secrecy rate is the utility function and the constraints are posed by the available power budget. Then we consider a pragmatic approach where we target the signal-to-noise ratio (SNR) of participating nodes and ensure information secrecy by appropriately constraining the SNRs of those nodes. In those SNR based formulations, SNR at the destination is the utility function and we are interested in maximizing it. In the last two chapters, we study two scenarios in a non-secrecy setting. In one of them, end-to-end data rate is the utility, whereas, in the other one, two utility functions|based on revenue generated|are defined for two rational agents in a game-theoretic setting. In the second chapter, we study parallel independent Gaussian channels with imperfect channel state information (CSI) for the eavesdropper. Firstly, we evaluate the probability of zero secrecy rate in this system for (i) given instantaneous channel conditions and (ii) a Rayleigh fading scenario. Secondly, when non-zero secrecy is achievable in the low SNR regime, we aim to solve a robust power allocation problem which minimizes the outage probability at a target secrecy rate. In the third, fourth and fifth chapters, we consider scenarios where the source node transmits a message to the destination using M parallel amplify-and-forward (AF) relays in the presence of a single or multiple eavesdroppers. The third chapter addresses the problem of the maximum achievable secrecy rate for two specific network models: (a) degraded eavesdropper channel with complex channel gain and (b) scaled eavesdropper channel with real-valued channel gains. In the fourth chapter, we consider the SNR based approach and address two problems: (i) SNR maximization at the destination and (ii) Total relay power minimization. In the fifth chapter, we assume that the relay nodes are untrusted and to counter them, we deliberately introduce artificial noise in the source message. For this model, we propose and solve SNR maximization problems for the following two scenarios: (i) Total power constraint on all the relay nodes and (ii) Individual power constraints on each of the relay nodes. In the sixth chapter, we address the problem of passive eavesdroppers in multi-hop wire-less networks using the technique of friendly jamming. Assuming decode-and-forward (DF) relaying, we consider a scheduling and power allocation (PA) problem for a multiple-source multiple-sink scenario so that eavesdroppers are jammed, and source-destination throughput targets are met. When channel state information (CSI) of all the node are available, we intend to minimize the total power consumption of all the transmitting nodes. In the absence of eavesdroppers CSI, we minimize vulnerability region of the network. In chapter seven, the problem of cooperative beamforming for maximizing the achievable data rate of two-hop amplify-and-forward (AF) network (in the absence of eavesdropper(s)) is considered. Along with an individual power constraint on each of the relay nodes, we consider a weighted sum power constraint. To solve this problem, we propose a novel algorithm based on the Quadratic Eigenvalue Problem (QEP) and discuss its convergence. In chapter eight, we study a Stackelberg game between a base station and a multi-antenna power beacon for wireless energy harvesting in a multiple sensor node scenario. Assuming imperfect CSI between the sensor nodes and the power beacon, we propose a utility function that is based on throughput non-outage probability at the base station. We find the optimal strategies for the base station and the power beacon that maximize their respective utility functions.
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