In practice, a communication system works with finite blocklength codes because of the delay constraints and the information-theoretic bounds which are proposed for finite blocklength systems can be exploited to determine the performance of a designed system. In this thesis, achievable rates for given average error probabilities are considered for finite blocklength systems. Although classical bounds can be used to upper bound the error probability, these bounds require the optimization of auxiliary variables. In this work, a bound which is called the dependence testing (DT) bound that is free of any auxiliary variables is exploited. The DT bound is evaluated by introducing a normal approximation to the information density. Simulations carried out both for the Gaussian and discrete input alphabets show the proposed approximation enables very good prediction of the achievable rates. The proposed approximation is also used to calculate the average error probability for block fading channels. Simulations performed for Rayleigh block fading channels demonstrate that the total blocklength of the system in addition to the number of fading blocks should be accounted for especially when the number of fading blocks is large. A power allocation problem in block fading channels when the channel state information is available to the transmitting side is investigated in the final part of this work. The DT bound is optimized for a given channel state vector by allocating different power levels to each fading block by exploiting short-term power allocation. A simple power allocation algorithm is proposed which comes out with very similar results compared with the analytically computed values.

The thesis presents research on multiobjective optimization based on memetic computing and its applications in engineering. We have introduced a framework for adaptive multiobjective memetic optimization algorithms (AMMOA) with an information theoretic criterion for guiding the selection, clustering, and local refinements. A robust stopping criterion for AMMOA has also been introduced to solve non-linear and large-scale optimization problems. The framework has been implemented for different benchmark test problems with remarkable results. This thesis also presents two applications of these algorithms. First, an optimal image data hiding technique has been formulated as a multiobjective optimization problem with conflicting objectives. In particular, trade-off factors in designing an optimal image data hiding are investigated to maximize the quality of watermarked images and the robustness of watermark. With the fixed size of a logo watermark, there is a conflict between these two objectives, thus a multiobjective optimization problem is introduced. We propose to use a hybrid between general regression neural networks (GRNN) and the adaptive multiobjective memetic optimization algorithm (AMMOA) to solve this challenging problem. This novel image data hiding approach has been implemented for many different test natural images with remarkable robustness and transparency of the embedded logo watermark. We also introduce a perceptual measure based on the relative Rényi information spectrum to evaluate the quality of watermarked images. The second application is the problem of joint spectrum sensing and power control optimization for a multichannel, multiple-user cognitive radio network. We investigated trade-off factors in designing efficient spectrum sensing techniques to maximize the throughput and minimize the interference. To maximize the throughput of secondary users and minimize the interference to primary users, we propose a joint determination of the sensing and transmission parameters of the secondary users, such as sensing times, decision threshold vectors, and power allocation vectors. There is a conflict between these two objectives, thus a multiobjective optimization problem is used again in the form of AMMOA. This algorithm learns to find optimal spectrum sensing times, decision threshold vectors, and power allocation vectors to maximize the averaged opportunistic throughput and minimize the averaged interference to the cognitive radio network. / February 2016

We consider a wireless communication system in which there are N transmitter-receiver pairs and each transmitter wants to communicate with its corresponding receiver. This is modelled as an interference channel. We propose power allocation algorithms for increasing the sum rate of two and three user interference channels. The channels experience fast fading and there is an average power constraint on each transmitter. In this case receivers use successive decoding under strong interference, instead of treating interference as noise all the time. Next, we u se game theoretic approach for power allocation where each receiver treats interference as noise. Each transmitter-receiver pair aims to maximize its long-term average transmission rate subject to an average power constraint. We formulate a stochastic game for this system in three different scenarios. First, we assume that each user knows all direct and crosslink channel gains. Next, we assume that each user knows channel gains of only the links that are incident on its receiver. Finally, we assume that each use r knows only its own direct link channel gain. In all cases, we formulate the problem of finding the Nash equilibrium(NE) as a variational in equality problem. For the game with complete channel knowledge, we present an algorithm to solve the VI and we provide weaker sufficient conditions for uniqueness of the NE than the sufficient conditions available in the literature. Later, we present a novel heuristic for solving the VI under general channel conditions. We also provide a distributed algorithm to compute Pare to optimal solutions for the proposed games. We use Bayesian learning that guarantees convergence to an Ɛ-Nash equilibrium for the incomplete information game with direct link channel gain knowledge only, that does not require knowledge of the power policies of other users but requires feedback of the interference power values from a receiver to its corresponding transmitter. Later, we consider a more practical scenario in which each transmitter transmits data at a certain rate using a power that depends on the channel gain to its receiver. If a receiver can successfully receive the message, it sends an acknowledgement(ACK), else it sends a negative ACK(NACK). Each user aims to maximize its probability of successful transmission. We formulate this problem as a stochastic game and propose a fully distributed learning algorithm to find a correlated equilibrium(CE). In addition, we use a no regret algorithm to find a coarse correlated equilibrium(CCE) for our power allocation game. We also propose a fully distributed learning algorithm to find a Pareto optimal solution. In general Pareto points do not guarantee fairness among the users. Therefore we also propose an algorithm to compute a Nash bargaining solution which is Pareto optimal and provides fairness among the users. Finally, we extend these results when each transmitter sends data at multiple rates rather than at a fixed rate.

Power allocation algorithms that determine how much power should be allocated to pilot and data symbols play an important role in addressing the trade-off between accurate channel estimation and high high spectral efficiency for data symbols in the presence of time-varying fading channels. Dealing with this trade-off is highly non-trivial when the channel changes or ages rapidly in time. Specifically, channel aging renders the often used assumption that the channel parameters can be regarded constant between channel estimation instances invalid. Previous works have addressed the problem of the pilot spacing problem for Rayleigh fading channels. In this work, a power control algorithm is developed for both Rayleigh fading and Rician fading channels to deal with the above trade-off. Specifically, in this report, the uplink channel of a multi-user multiple input multiple output system is investigated. The fading channel is estimated by a suitable auto-regressive model using the associated auto-correlation function. Then the signal-to-interference-plus-noise ratio and spectral efficiency are calculated as a function of the power allocation ratio and other parameters of the communication network. The proposed power control algorithm is designed to find the upper bound of the spectral efficiency. As application examples, two uncrewed aerial vehicle networks are also modeled, in which the performance of the proposed power control algorithm is simulated to find how the parameters of the network will influence the algorithm results. Our investigation shows that the proposed power control algorithm performs well in the presence of fading communication channels and outperforms the benchmark case of equal power allocation between pilot and data symbols. / Effektallokeringsalgoritmen som bestämmer hur mycket effekt som ska allokeras till pilotsymboler och datasymboler är mycket viktig för att fånga avvägningen mellan korrekt kanaluppskattning och ett högt signal till störnings plus brusförhållande för en tidsvarierande fädning kanal. Tidigare arbete har löst problemet med pilotavstånds-problemet för Rayleigh fädning kanaler. I detta arbete genereras effektstyrnings-algoritmen för både Rayleigh fading och Rician fädning kanaler för att hantera avvägningen. I denna rapport genereras först en upplänkskanal för ett fleranvändarsystem med flera ingångar med flera utdata. Fädningskanalen uppskattas av den autoregressiva modellen med hjälp av autokorrelations funktionen. Sedan beräknas signal till interferens plus brusförhållandet och spektral effektivitet som en funktion av effekttilldelnings förhållandet och andra parametrar för kommunikationsnätverket. Effektstyrnings algoritmen är att hitta den övre gränsen för den spektrala effektiviteten. I detta arbete modelleras också två obemannade flygfordonsnätverk och prestanda för effektstyrningsalgoritmen simuleras också på dessa två modeller för att hitta hur nätverkets parametrar kommer att påverka algoritmresultaten.

The atmospheric lightwave propagation is considerably influenced by the random variations in the refractive index of air pockets due to turbulence. This undesired effect significantly degrades the performance of free-space optical (FSO) communication systems. Interestingly, the severity of such random degradations is highly related to the range of atmospheric propagation. In this thesis, we introduce relay-assisted FSO communications as a very promising technique to combat the degradation effects of atmospheric turbulence. Considering different configurations of the relays, we quantify the outage behavior of the relay-assisted system and identify the optimum relaying scheme. We further optimize the performance of the relay-assisted FSO system subject to some power constraints and provide optimal power control strategies for different scenarios under consideration. Moreover, an application of FSO relaying technique in quantum communications is investigated. The results demonstrate impressive performance improvements for the proposed relay-assisted FSO systems with respect to the conventional direct transmission whether applied in a classical or a quantum communication channel.

As wireless communication becomes an ever-more important and pervasive part of our everyday life, system capacity and quality of service issues are becoming more critical. In order to increase the system capacity and improve the quality of service, it is necessary that we pay closer attention to bandwidth and power efficiency issues. Orthogonal Frequency Division Multiplexing (OFDM) is a multicarrier modulation technique for high speed data transmission and is generally regarded as bandwidth efficient. However, OFDM signals suffer from high peak-to-average power ratios (PARs) which lead to power inefficiency in the RF portion of the transmitter. Moreover, in OFDM, the well-known pilot tone assisted modulation (PTAM) technique utilizes a number of dedicated training pilots to acquire the channel state information (CSI), resulting in somewhat reduced bandwidth efficiency. In this dissertation, we will address the above mentioned bandwidth and power efficiency issues in wireless transmissions. To avoid bandwidth efficiency loss due to dedicated training, we will first develop a superimposed training framework that can be used to track the frequency selective as well as the Doppler shift characteristics of a channel. Later on, we will propose a generalized superimposed training framework that allows improved channel estimates. To improve the power efficiency, we adopt the selected mapping (SLM) framework to reduce the PARs for both OFDM and forward link Code Division Multiple Access (CDMA). We first propose a dynamic SLM algorithm to greatly reduce the computational requirement of SLM without sacrificing its PAR reducing capability. We propose a number of blind SLM techniques for OFDM and for forward link CDMA; they require no side information and are easy to implement. Our proposed blind SLM technique for OFDM is a novel joint channel estimation and PAR reduction algorithm, for which bandwidth efficiency power efficiency - complexity - bit error rate tradeoffs are carefully considered.

Cooperative relaying is a promising diversity achieving technique to provide reliable transmission, high throughput and extensive coverage for wireless networks in a variety of applications. Two-way relaying is a spectrally efficient protocol, providing one solution to overcome the half-duplex loss in one-way relay channels. Moreover, incorporating the multiple-input-multiple-output (MIMO) technology can further improve the spectral efficiency and diversity gain. A lot of related work has been performed on the two-way relay network (TWRN), but most of them assume perfect channel state information (CSI). In a realistic scenario, however, the channel is estimated and the estimation error exists. So in this thesis, we explicitly take into account the CSI error, and investigate its impact on the performance of amplify-and-forward (AF) TWRN where either multiple distributed single-antenna relays or a single multiple-antenna relay station is exploited. For the distributed relay network, we consider imperfect self-interference cancellation at both sources that exchange information with the help of multiple relays, and maximal ratio combining (MRC) is then applied to improve the decision statistics under imperfect signal detection. The system performance degradation in terms of outage probability and average bit-error rate (BER) are analyzed, as well as their asymptotic trend. To further improve the spectral efficiency while maintain the spatial diversity, we utilize the maximum minimum (Max-Min) relay selection (RS), and examine the impact of imperfect CSI on this single RS scheme. To mitigate the negative effect of imperfect CSI, we resort to adaptive power allocation (PA) by minimizing either the outage probability or the average BER, which can be cast as a Geometric Programming (GP) problem. Numerical results verify the correctness of our analysis and show that the adaptive PA scheme outperforms the equal PA scheme under the aggregated effect of imperfect CSI. When employing a single MIMO relay, the problem of robust MIMO relay design has been dealt with by considering the fact that only imperfect CSI is available. We design the MIMO relay based upon the CSI estimates, where the estimation errors are included to attain the robust design under the worst-case philosophy. The optimization problem corresponding to the robust MIMO relay design is shown to be nonconvex. This motivates the pursuit of semidefinite relaxation (SDR) coupled with the randomization technique to obtain computationally efficient high-quality approximate solutions. Numerical simulations compare the proposed MIMO relay with the existing nonrobust method, and therefore validate its robustness against the channel uncertainty. / Graduate

The atmospheric lightwave propagation is considerably influenced by the random variations in the refractive index of air pockets due to turbulence. This undesired effect significantly degrades the performance of free-space optical (FSO) communication systems. Interestingly, the severity of such random degradations is highly related to the range of atmospheric propagation. In this thesis, we introduce relay-assisted FSO communications as a very promising technique to combat the degradation effects of atmospheric turbulence. Considering different configurations of the relays, we quantify the outage behavior of the relay-assisted system and identify the optimum relaying scheme. We further optimize the performance of the relay-assisted FSO system subject to some power constraints and provide optimal power control strategies for different scenarios under consideration. Moreover, an application of FSO relaying technique in quantum communications is investigated. The results demonstrate impressive performance improvements for the proposed relay-assisted FSO systems with respect to the conventional direct transmission whether applied in a classical or a quantum communication channel.

Multipath propagation and mobility in wireless communication systems give rise to variations in the amplitude and phase of the transmitted signal, commonly referred to as fading. Many wireless applications are affected by slowly varying fading, where the channel is non-ergodic, leading to non-reliable transmission during bad channel realizations. These communication scenarios are well modeled by the block-fading channel, where the reliability is quantatively characterized by the outage probability. This thesis focuses on the analysis and design of adaptive transmission schemes to improve the outage performance of both single- and multiple-antenna transmission over the block-fading channel, especially for the cases where discrete input constellations are used. Firstly, a new lower bound on the outage probability of non-adaptive transmission is proposed, providing an efficient tool for evaluating the performance of non-adaptive transmission. The lower bound, together with its asymptotic analysis, is essential for efficiently designing the adaptive transmission schemes considered in the thesis. Secondly, new power allocation rules are derived to minimize the outage probability of fixed-rate transmission over block-fading channels. Asymptotic outage analysis for the resulting schemes is performed, revealing important system design criteria. Furthermore, the thesis proposes novel suboptimal power allocation rules, which enjoy low-complexity while suffering minimal losses as compared to the optimal solution. Thus, these schemes facilitate power adaptation in low-cost devices. Thirdly, the thesis considers incremental-redundancy automatic-repeat-request (INR-ARQ) strategies, which perform adaptive transmission based on receiver feedback. In particular, the thesis concentrates on multi-bit feedback, which has been shown to yield significant gains in performance compared to conventional single-bit ARQ schemes. The thesis proposes a new information-theoretic framework for multi-bit feedback INR-ARQ, whereby the receiver feeds back a quantized version of the accumulated mutual information. Within this framework, the thesis presents an asymptotic analysis which yields the large gains in outage performance offered by multi-bit feedback. Furthermore, the thesis proposes practical design rules, which further illustrates the benefits of multi-bit feedback in INR-ARQ systems. In short, the thesis studies the outage performance of transmission over block-fading channels. Outage analysis is performed for non-adaptive and adaptive transmission. Improvements for the existing adaptive schemes are also proposed, leading to either lower complexity requirements or better outage performance. Still, further research is needed to bring the benefits offered by adaptive transmission into practical systems. / Thesis (PhD)--University of South Australia, 2010

Multipath propagation and mobility in wireless communication systems give rise to variations in the amplitude and phase of the transmitted signal, commonly referred to as fading. Many wireless applications are affected by slowly varying fading, where the channel is non-ergodic, leading to non-reliable transmission during bad channel realizations. These communication scenarios are well modeled by the block-fading channel, where the reliability is quantatively characterized by the outage probability. This thesis focuses on the analysis and design of adaptive transmission schemes to improve the outage performance of both single- and multiple-antenna transmission over the block-fading channel, especially for the cases where discrete input constellations are used. Firstly, a new lower bound on the outage probability of non-adaptive transmission is proposed, providing an efficient tool for evaluating the performance of non-adaptive transmission. The lower bound, together with its asymptotic analysis, is essential for efficiently designing the adaptive transmission schemes considered in the thesis. Secondly, new power allocation rules are derived to minimize the outage probability of fixed-rate transmission over block-fading channels. Asymptotic outage analysis for the resulting schemes is performed, revealing important system design criteria. Furthermore, the thesis proposes novel suboptimal power allocation rules, which enjoy low-complexity while suffering minimal losses as compared to the optimal solution. Thus, these schemes facilitate power adaptation in low-cost devices. Thirdly, the thesis considers incremental-redundancy automatic-repeat-request (INR-ARQ) strategies, which perform adaptive transmission based on receiver feedback. In particular, the thesis concentrates on multi-bit feedback, which has been shown to yield significant gains in performance compared to conventional single-bit ARQ schemes. The thesis proposes a new information-theoretic framework for multi-bit feedback INR-ARQ, whereby the receiver feeds back a quantized version of the accumulated mutual information. Within this framework, the thesis presents an asymptotic analysis which yields the large gains in outage performance offered by multi-bit feedback. Furthermore, the thesis proposes practical design rules, which further illustrates the benefits of multi-bit feedback in INR-ARQ systems. In short, the thesis studies the outage performance of transmission over block-fading channels. Outage analysis is performed for non-adaptive and adaptive transmission. Improvements for the existing adaptive schemes are also proposed, leading to either lower complexity requirements or better outage performance. Still, further research is needed to bring the benefits offered by adaptive transmission into practical systems. / Thesis (PhD)--University of South Australia, 2010