The scarce and overpopulated radio spectrum is going to present a major barrier to the growth and development of future wireless networks. As such, spectrum sharing seems to be inevitable to accommodate the exploding demand for high data rate applications. A major challenge to realizing the potential advantages of spectrum sharing is interference management. This thesis deals with interference management techniques in noncooperative networks. In specific, interference alignment is used as a powerful technique for interference management. We use the degrees of freedom (DoF) as the figure of merit to evaluate the performance improvement due to the interference management schemes. This dissertation is organized in two parts. In the first part, we consider the K-user multiple input multiple output (MIMO) Gaussian interference channel (IC) with M antennas at each transmitter and N antennas at each receiver. This channel models the interaction between K transmitter-receiver pairs sharing the same spectrum for data communication. It is assumed that the channel coefficients are constant and are available at all nodes prior to data transmission. A new cooperative upper-bound on the DoF of this channel is developed which outperforms the known bounds. Also, a new achievable transmission scheme is provided based on the idea of interference alignment. It is shown that the achievable DoF meets the upper-bound when the number of users is greater than a certain threshold, and thus it reveals the channel DoF. In the second part, we consider communication over MIMO interference and X channels in a fast fading environment. It is assumed that the transmitters obtain the channel state information (CSI) after a finite delay which is greater than the coherence time of the channel. In other words, the CSI at the transmitters becomes outdated prior to being exploited for the current transmission. New transmission schemes are proposed which exploit the knowledge of the past CSI at the transmitters to retrospectively align interference in the subsequent channel uses. The proposed transmission schemes offer DoF gain compared to having no CSI at transmitters. The achievable DoF results are the best known results for these channels. Simple cooperative upper-bounds are developed to prove the tightness of our achievable results for some network configurations.

En els sistemes de comunicacions on el transmissor disposa de certa informació sobre l'estat del canal (CSI), es possible dissenyar esquemes lineals de precodificació que assignin la potència de manera òptima induint guanys considerables, sigui en termes de capacitat, sigui en termes de la fiabilitat de l'enllaç de comunicacions. A la pràctica, aquest coneixement del canal mai és perfecte i, per tant, el senyal transmès es veurà degradat degut al desajust entre la informació que el transmissor disposi del canal i el seu estat real.En aquest context, aquesta tesi estudia dos problemes diferents però alhora estretament relacionats: el disseny d'un esquema pràctic de seguiment del canal en transmissió per canals variants en temps, i el disseny d'esquemes lineals de precodificació que siguin robustos a la incertesa del canal. La primera part de la tesi proposa el disseny d'un esquema de seguiment de canal que, mitjançant un enllaç de retorn de baixa capacitat, proporcioni al transmissor una informació acurada sobre el seu estat. Històricament, aquest tipus d'esquemes han rebut fortes crítiques degut a la gran quantitat d'informació que és necessari transmetre des del receptor cap el transmissor. Aquesta tesi, doncs, posa especial èmfasi en el disseny d'aquest canal de retorn. La solució que es proposa, basada en el filtre de Kalman, utilitza un esquema que recorda al transmissor DPCM. Les variacions del canal són tractades mitjançant dos predictors lineals idèntics situats en el transmissor i en el receptor, i un canal de retorn que assisteix el transmissor amb l'error de predicció. L'interès d'aquest esquema diferencial és que permet seguir les variacions del canal amb només dos o quatre bits per coeficient complex, fins i tot en canals ràpidament variants.La resta de la tesi cobreix el segon objectiu, l'estudi de diferents esquemes d'assignació de potències quan el coneixement del canal en transmissió no és perfecte. El problema es planteja per a un sistema MIMO OFDM com a formulació més general, incloent els casos d'una sola antena, de l'esquema beamforming i del canal multiplicatiu com a casos particulars.Primerament s'ha plantejat l'optimització dels criteris de mínim error quadràtic mig (MMSE) i mínima BER sense codificar. La innovació en el treball presentat a la tesi, respecte a altres treballs que segueixen els mateixos criteris de disseny, ha estat la formulació Bayesiana del problema per al disseny dels algoritmes robustos.La tesi continua amb el plantejament d'estratègies robustes d'assignació de potència destinades a minimitzar la BER codificada. Per aquesta tasca s'han utilitzat criteris de teoria de la informació. Possiblement una de les principals contribucions d'aquesta tesi ha estat el plantejament del cut-off rate com a paràmetre de disseny. Aquest criteri s'introdueix com alternativa a la capacitat de canal o a la informació mutual per al disseny del transmissor quan s'inclou codificació de canal. La ultima part de la tesi proposa un interleaver adaptatiu de baixa complexitat que, utilitzant el coneixement del canal disponible en el transmissor, assigna estratègicament els bits no només per combatre les ràfegues d'errors, sinó també per lluitar contra els esvaïments que puguin presentar les diferents portadores del canal per a una realització concreta. El disseny d'aquest interleaver, anomenat "interleaver RCPC" està basat en els codis Rate-Compatible Punctured Convolutional Codes. Com s'il·lustra a partir del resultats numèrics, l'ús d'aquest interleaver millora les prestacions dels algoritmes quan es comparen amb les que s'obtindrien si s'utilitzes un interleaver de bloc o un interleaver pseudo-aleatori. / When the transmitter of a communication system disposes of some Channel State Information (CSI), it is possible to design linear precoders that optimally allocate the power inducing high gains either in terms of capacity or in terms of reliable communications. In practical scenarios, this channel knowledge is not perfect and thus the transmitted signal suffers from the mismatch between the CSI at the transmitter and the real channel.In that context, this thesis deals with two different, but related, topics: the design of a feasible transmitter channel tracker for time varying channels, and the design of optimal linear precoders robust to imperfect channel estimates.The first part of the thesis proposes the design of a channel tracker that provides an accurate CSI at the transmitter by means of a low capacity feedback link. Historically, those schemes have been criticized because of the large amount of information to be transmitted from the receiver to the transmitter. This thesis focuses, thus, the attention in an accurate design of the return link. The proposed solution is based on the Kalman filter and follows a scheme that reminds the well known DPCM transmitter. The channel variability is processed by two identical linear predictors located at the transmitter and at the receiver, and a feedback link that assists the transmitter with the prediction error. The interest of this differential scheme is that allows to track the channel variations with only two or four bits per complex channel coefficient even in fast time-varying channels.The rest of the thesis covers the second topic, studying different robust power allocation algorithms when the CSI is not perfectly known at the transmitter. For the sake of generality, the problem is formulated for the general MIMO OFDM case, encompassing the single antenna transmission, the beamforming schemes and the frequency-flat fading channels as particular cases. First, the minimum MSE and the minimum uncoded BER parameters are chosen to be optimized, evaluating the performance of the algorithms in terms of uncoded BER. The basic novelty with respect to previous works that considers the same strategies of design is the proposal of a Bayesian approach for the design of the robust algorithms.Next the study is extended by proposing robust power allocation strategies focused on the minimization of the coded BER. For this purpose, information-theoretic criteria are used. Probably, one of the main contributions in the thesis is the proposal of the cut-off rate as a parameter of design whose maximization is directly related to the coded BER. This criterion is introduced as an alternative to the channel capacity and the mutual information for the design of optimal transceivers in the presence of any channel coding stage. The last part of the thesis proposes a low complexity adaptive interleaver that, making use of the CSI available at the transmitter, reallocates the bits not only to combat the bursty channel errors but also to combat the specific distribution of the faded subcarriers as a function of the channel response. The design of this interleaver, named as "RCPC interleaver", is based on the Rate-Compatible Punctured Convolutional Codes. As shown by numerical results, the use of this interleaver improves the performance of the algorithms when they are compared with the classical block interleavers and pseudo-random interleavers.

The scarce and overpopulated radio spectrum is going to present a major barrier to the growth and development of future wireless networks. As such, spectrum sharing seems to be inevitable to accommodate the exploding demand for high data rate applications. A major challenge to realizing the potential advantages of spectrum sharing is interference management. This thesis deals with interference management techniques in noncooperative networks. In specific, interference alignment is used as a powerful technique for interference management. We use the degrees of freedom (DoF) as the figure of merit to evaluate the performance improvement due to the interference management schemes. This dissertation is organized in two parts. In the first part, we consider the K-user multiple input multiple output (MIMO) Gaussian interference channel (IC) with M antennas at each transmitter and N antennas at each receiver. This channel models the interaction between K transmitter-receiver pairs sharing the same spectrum for data communication. It is assumed that the channel coefficients are constant and are available at all nodes prior to data transmission. A new cooperative upper-bound on the DoF of this channel is developed which outperforms the known bounds. Also, a new achievable transmission scheme is provided based on the idea of interference alignment. It is shown that the achievable DoF meets the upper-bound when the number of users is greater than a certain threshold, and thus it reveals the channel DoF. In the second part, we consider communication over MIMO interference and X channels in a fast fading environment. It is assumed that the transmitters obtain the channel state information (CSI) after a finite delay which is greater than the coherence time of the channel. In other words, the CSI at the transmitters becomes outdated prior to being exploited for the current transmission. New transmission schemes are proposed which exploit the knowledge of the past CSI at the transmitters to retrospectively align interference in the subsequent channel uses. The proposed transmission schemes offer DoF gain compared to having no CSI at transmitters. The achievable DoF results are the best known results for these channels. Simple cooperative upper-bounds are developed to prove the tightness of our achievable results for some network configurations.

The demand for mobile wireless network resources is constantly on the rise, pushing for new communication technologies that are able to support unprecedented rates. In this thesis we address the issue by considering advanced interference management techniques to exploit the available resources more efficiently under relaxed channel state information (CSI) assumptions. While the initial studies focus on current half-duplex (HD) technology, we then move on to full-duplex (FD) communication due to its inherent potential to improve spectral efficiency. Work in this thesis is divided into four main parts as follows. In the first part, we focus on the two-cell two-user-per-cell interference broadcast channel (IBC) and consider the use of topological interference management (TIM) to manage inter-cell interference in an alternating connectivity scenario. Within this context we derive novel outer bounds on the achievable degrees of freedom (DoF) for different system configurations, namely, single-input single-output (SISO), multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) systems. Additionally, we propose new transmission schemes based on joint coding across states that exploit global topological information at the transmitter to increase achievable DoF. Results show that when a single state has a probability of occurrence equal to one, the derived bounds are tight with up to a twofold increase in achievable DoF for the best case scenario. Additionally, when all alternating connectivity states are equiprobable: the SISO system gains 11/16 DoF, achieving 96:4% of the derived outer bound; while the MISO/MIMO scenario has a gain of 1/2 DoF, achieving the outer bound itself. In the second part, we consider a general G-cell K-user-per-cell MIMO IBC and analyse the performance of linear interference alignment (IA) under imperfect CSI. Having imperfect channel knowledge impacts the effectiveness of the IA beamformers, and leads to a significant amount of residual leakage interference. Understanding the extent of this impact is a fundamental step towards obtaining a performance characterisation that is more relevant to practical scenarios. The CSI error model used is highly versatile, allowing the error to be treated either as a function of the signal-to-noise ratio (SNR) or as independent of it. Based on this error model, we derive a novel upper bound on the asymptotic mean sum rate loss and quantify the DoF loss due to imperfect CSI. Furthermore, we propose a new version of the maximum signal-to-interference plus noise ratio (Max-SINR) algorithm which takes into account statistical knowledge of the CSI error in order to improve performance over the naive counterpart in the presence of CSI mismatch. In the third part, we shift our attention to FD systems and consider weighted sum rate (WSR) maximisation for multi-user multi-cell networks where FD base-stations (BSs) communicate with HD downlink (DL) and uplink (UL) users. Since WSR problems are non-convex we transform them into weighted minimum mean squared error (WMMSE) ones that are proven to converge. Our analysis is first carried out for perfect CSI and then expanded to cater for imperfect CSI under two types of error models, namely, a norm-bounded error model and a stochastic error model. Additionally, we propose an algorithm that maximises the total DL rate subject to each UL user achieving a desired target rate. Results show that the use of FD BSs provides significant gains in achievable rate over the use of HD BSs, with a gain of 1:92 for the best case scenario under perfect CSI. They also demonstrate the robust performance of the imperfect CSI designs, and confirm that FD outperforms HD even under CSI mismatch conditions. Finally, the fourth part considers the use of linear IA to manage interference in a multi-user multi-cell network with FD BSs and HD users under imperfect CSI. The number of interference links present in such a system is considerably greater than that present in the HD network counterpart; thus, understanding the impact of residual leakage interference on performance is even more important for FD enabled networks. Using the same generalised CSI error model from the second part, we study the performance of IA by characterising the sum rate and DoF losses incurred due to imperfect CSI. Additionally, we propose two novel IA algorithms applicable to this network; the first one is based on minimising the mean squared error (MMSE), while the second is based on Max-SINR. The proposed algorithms exploit statistical knowledge of the CSI error variance in order to improve performance. Moreover, they are shown to be equivalent under certain conditions, even though the MMSE based one has lower computational complexity. Furthermore for the multi-cell case, we also derive the proper condition for IA feasibility.

Dans la première partie de la thèse, on se concentre sur la conception d'un système de communication par satellite complet se basant sur la construction de faisceaux adaptatifs aux terminaux mobiles. Comparé à la construction classique de faisceaux fixes, le système à faisceaux adaptatifs peut considérablement améliorer la capacité du système en termes du nombre de STs desservies et de l'efficacité énergétique. Pour la conception du système à faisceaux adaptatifs, les informations sur l'état de canal (CSI) sont essentielles. Vu que le temps de propagation est trop long par rapport au temps de cohérence du canal, le CSI instantané est déjà périmé lorsqu'il est reçu pour la construction des faisceaux. Cependant, une partie de l'information du canal, plus particulièrement, les vecteurs de directivité ont une variation assez lente. On utilise cette connaissance partielle du CSI pour concevoir le système à base de faisceaux adaptatifs. Afin d'estimer les vecteurs de directivité, on propose un algorithme basé sur un critère de minimisation de l'erreur quadratique. Puis, basées sur l'estimation des vecteurs de directivité, on présente deux approches heuristiques pour la conception des faisceaux. En outre, on propose également deux approches qui reposent sur l'estimation de la directivité pour la détection des STs et la résolution possible des collisions sur le canal d'accès aléatoire au satellite. Comme la performance du système SDMA dépend fortement des positions spatiales des STs co-existants, on propose deux algorithmes de faible complexité pour l'attribution des fréquences dans le système de communication par satellite / In the first part of the thesis, we focus on the design of a complete satellite communication system adopting adaptive beamforming with mobile satellite terminals. Compared with conventional fixed beamforming, adaptive beamforming can signi_cantly improve the capacity of a satellite system in terms of served satellite terminals (ST) and power e_ciency. For the design of an adaptive beamforming system, channel state information (CSI) is critical. Since the propagation delay is too long compared to the coherence time of the channel, the instantaneous CSI is already stale when processed for beamforming. However, some parts of the channel, more speci_cally, directivity vectors change quite slowly. We utilize this partial knowledge of CSI to design an adaptive beamforming system. In order to estimate the directivity vectors, we propose an algorithm based on a least square error criterion. Then, based on the estimation of directivity vectors, we propose two heuristics approaches to the design of adaptive beamforming. Additionally, we also propose two approaches, based on directivity estimation for the detection of transmitting terminals and the possible resolution of collisions in the random access channel of the satellite system. Since SDMA system performance depends strongly on the spatial locations of co-existing terminals, we also propose two low complexity algorithms for frequency allocation in a satellite communication system. Finally, we simulate a complete satellite system, including a random access channel and a connection-oriented channel. We analyze the system performance and compare it to conventional fixed beamforming systems

The history of Software-Defined Radios (SDRs) epitomizes innovation in wireless communication. Initially serving military needs, SDRs swiftly transitioned to civilian applications, revolutionizing communication. This thesis explores SDR applications such as Spectrum Scanning Systems, Contraband Cellphone Detection, and Human Activity Recognition via Wi-Fi signals. SDRs empower Spectrum Scanning Systems to monitor and analyze radio frequencies, optimizing spectrum allocation for seamless wireless communication. In Contraband Cellphone Detection, SDRs identify unauthorized signals in restricted areas, bolstering security efforts by thwarting illicit cellphone usage. Human Activity Recognition utilizes Raspberry Pi 3B+ to track movement patterns via Wi-Fi signals, offering insights across various sectors. Additionally, the thesis conducts a comparative analysis of Wi-Fi-based Human Activity Recognition and Radar for accuracy assessment. SDRs continue to drive innovation, enhancing wireless communication and security in diverse domains, from defense to healthcare and beyond.

In wireless communication systems, the use of multiple antennas, also known as Multiple-Input Multiple-Output(MIMO) communications, is now a widely accepted and important technology for improving their reliability and throughput performance. However, in order to achieve the performance gains predicted by the theory, the transmitter and receiver need to have accurate and up-to-date Channel State Information(CSI) to overcome the vagaries of the fading environment. Traditionally, the CSI is obtained at the receiver by sending a known training sequence in the forward-link direction. This CSI has to be conveyed to the transmitter via a low-rate, low latency and noisy feedback channel in the reverse-link direction. This thesis addresses three key challenges in sending the CSI to the transmitter of a MIMO communication system over the reverse-link channel, and provides novel solutions to them. The first issue is that the available CSI at the receiver has to be quantized to a finite number of bits, sent over a noisy feedback channel, reconstructed at the transmitter, and used by the transmitter for precoding its data symbols. In particular, the CSI quantization technique has to be resilient to errors introduced by the noisy reverse-link channel, and it is of interest to design computationally simple, linear filters to mitigate these errors. The second issue addressed is the design of low latency and low decoding complexity error correction codes to provide protection against fading conditions and noise in the reverse-link channel. The third issue is to improve the resilience of the reverse-link channel to fading. The solution to the first problem is obtained by proposing two classes of receive filtering techniques, where the output of the source decoder is passed through a filter designed to reduce the overall distortion including the effect of the channel noise. This work combines the high resolution quantization theory and the optimal Minimum Mean Square Error(MMSE) filtering formulation to analyze, and optimize, the total end-to-end distortion. As a result, analytical expressions for the linear receive filters are obtained that minimize the total end-to-end distortion, given the quantization scheme and source(channel state) distribution. The solution to the second problem is obtained by proposing a new family of error correction codes, termed trellis coded block codes, where a trellis code and block code are concatenated in order to provide good coding gain as well as low latency and low complexity decoding. This code construction is made possible due to the existence of a uniform partitioning of linear block codes. The solution to the third problem is obtained by proposing three novel transmit precoding methods that are applicable to time-division-duplex systems, where the channel reciprocity can be exploited in designing the precoding scheme. The proposed precoding methods convert the Rayleigh fading MIMO channel into parallel Additive White Gaussian Noise(AWGN) channels with fixed gain, while satisfying an average transmit power constraint. Moreover, the receiver does not need to have knowledge of the CSI in order to decode the received data. These precoding methods are also extended to Rayleigh fading multi-user MIMO channels. Finally, all the above methods are applied to the problem of designing a low-rate, low-latency code for the noisy and fading reverse-link channel that is used for sending the CSI. Simulation results are provided to demonstrate the improvement in the forward-link data rate due to the proposed methods. Note that, although the three solutions are presented in the context of CSI feedback in MIMO communications, their development is fairly general in nature, and, consequently, the solutions are potentially applicable in other communication systems also.

The research reported in this thesis is concerned with robust precoder and transceiver optimization in multiuser multi-antenna wireless communication systems in the presence of imperfect channel state information(CSI). Precoding at the transmit side, which utilizes the CSI, can improve the system performance and simplify the receiver design. Transmit precoding is essential for inter-user interference cancellation in multiuser downlink where users do not cooperate. Linear and non-linear precoding have been widely investigated as low-complexity alternatives to dirty paper coding-based transmission scheme for multiuser multiple-input multiple-output(MU-MIMO)downlink. Similarly, in relay-assisted networks, precoding at the relay nodes have been shown to improve performance. The precoder and joint precoder/receive filter (transceiver) designs usually assume perfect knowledge of the CSI. In practical systems, however, the CSI will be imperfect due to estimation errors, feedback errors and feedback delays. Such imperfections in CSI will lead to deterioration of performance of the precoders/transceivers designed assuming perfect CSI. In such situations, designs which are robust to CSI errors are crucial to realize the potential of multiuser multi-antenna systems in practice. This thesis focuses on the robust designs of precoders and transceivers for MU-MIMO downlink, and for non-regenerative relay networks in the presence of errors in the CSI. We consider a norm-bounded error(NBE) model, and a stochastic error(SE) model for the CSI errors. These models are suitable for commonly encountered errors, and they allow mathematically and computationally tractable formulations for the robust designs. We adopt a statistically robust design in the case of stochastic error, and a minimax or worst-case robust design in the case of norm-bounded error. We have considered the robust precoder and transceiver designs under different performance criteria based on transmit power and quality-of-service(QoS) constraints. The work reported in this thesis can be grouped into three parts, namely,i ) robust linear pre-coder and transceiver designs for multiuser downlink, ii)robust non-linear precoder and transceiver designs for multiuser downlink, and iii)robust precoder designs for non-regenerative relay networks. Linear precoding: In this part, first, a robust precoder for multiuser multiple-input single-output(MU-MISO)downlink that minimizes the total base station(BS)transmit power with constraints on signal-to-interference-plus-noise ratio(SINR) at the user terminals is considered. We show that this problem can be reformulated as a second order cone program(SOCP) with the same order of computational complexity as that of the non-robust precoder design. Next, a robust design of linear transceiver for MU-MIMO downlink is developed. This design is based on the minimization of sum mean square error(SMSE) with a constraint on the total BS transmit power, and assumes that the error in the CSI at the transmitter(CSIT) follows the stochastic error model. For this design, an iterative algorithm based on the associated Karush-Kuhn-Tucker(KKT) conditions is proposed. Our numerical results demonstrate the robust performance of the propose designs. Non-linear precoding: In this part, we consider robust designs of Tomlinson-Harashima precoders(THP) for MU-MISO and MU-MIMO downlinks with different performance criteria and CSI error models. For MU-MISO systems with imperfect CSIT, we investigate the problem of designing robust THPs under MSE and total BS transmit power constraints. The first design is based on the minimization of total BS transmit power under constraints on the MSE at the individual user receivers. We present an iterative procedure to solve this problem, where each iteration involves the solution of a pair of convex optimization problems. The second design is based on the minimization of a stochastic function of the SMSE under a constraint on the total BS transmit power. We solve this problem efficiently by the method of alternating optimization. For MU-MIMO downlink, we propose robust THP transceiver designs that jointly optimize the TH precoder and receiver filters. We consider these transceiver designs under stochastic and norm-bounded error models for CSIT. For the SE model, we propose a minimum SMSE transceiver design. For the NBE model, we propose three robust designs, namely, minimum SMSE design, MSE-constrained design, and MSE-balancing design. Our proposed solutions to these robust design problems are based on iteratively solving a pair of sub-problems, one of which can be solved analytically, and the other can be formulated as a convex optimization problem that can be solved efficiently. Robust precoder designs for non-regenerative relay networks: In this part, we consider robust designs for two scenarios in the case of relay-assisted networks. First, we consider a non-regenerative relay network with a source-destination node pair assisted by multiple relay nodes, where each node is equipped with a single antenna. The set of the cooperating relay nodes can be considered as a distributed antenna array. For this scenario, we present a robust distributed beam former design that minimizes the total relay transmit power with a constraint on the SNR at the destination node. We show that this robust design problem can be reformulated as a semi-definite program (SDP)that can be solved efficiently. Next, we consider a non-regenerative relay network, where a set of source-destination node pairs are assisted by a MIMO-relay node, which is equipped with multiple transmit and multiple receive antennas. For this case, we consider robust designs in the presence of stochastic and norm-bounded CSI errors. We show that these problems can be reformulated as convex optimization problems. In the case of norm-bounded error, we use an approximate expression for the MSE in order to obtain a tractable solution.

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.

Motivated by the increasing demand for higher data rates, coverage, and spectral efficiency, current and next generation wireless systems adapt transmission parameters and even who is being transmitted to, based on the instantaneous channel states. For example, frequency-domain scheduling(FDS) is an instance of adaptation in orthogonal frequency division multiple access(OFDMA) systems in which the base station opportunistically assigns different subcarriers to their most appropriate user. Likewise ,transmit antenna selection(AS) is another form of adaptation in which the transmitter adapts which subset of antennas it transmits with. Cognitive radio(CR), which is a next generation technology, itself is a form of adaptation in which secondary users(SUs) adapt their transmissions to avoid interfering with the licensed primary users(PUs), who own the spectrum. However, adaptation requires channel state information(CSI), which might not be available apriori at the node or nodes that are adapting. Further, the CSI might not be perfect due to noise or feedback delays. This can result in suboptimal adaptation in OFDMA systems or excessive interference at the PUs due to transmissions by the SUs in CR. In this thesis, we focus on adaptation techniques in current and next generation wireless systems and evaluate the impact of CSI –both perfect and imperfect –on it. We first develop a novel model and analysis for characterizing the performance of AS in frequency-selective OFDMA systems. Our model is unique and comprehensive in that it incorporates key LTE features such as imperfect channel estimation based on dense, narrow band demodulation reference signal and coarse, broad band sounding reference signal. It incorporates the frequency-domain scheduler, the hardware constraint that the same antenna must be used to transmit over all the subcarriers that are allocated to a user, and the scheduling constraint that the allocated subcarriers must all be contiguous. Our results show the effectiveness of combined AS and FDS in frequency-selective OFDMA systems even at lower sounding reference signal powers. We then investigate power adaptation in underlay CR, in which the SU can transmit even when the primary is on but under stringent interference constraints. The nature of the interference constraint fundamentally decides how the SU adapts its transmit power. To this end, assuming perfect CSI, we propose optimal transmit power adaptation policies that minimize the symbol error probability of an SU when they are subject to different interference and transmit power constraints. We then study the robustness of these optimal policies to imperfections in CSI. An interesting observation that comes out of our study is that imperfect CSI can not only increase the interference at the PU but can also decrease it, and this depends on the choice of the system parameters, interference, and transmit power constraints. The regimes in which these occur are characterized.