Interference dominated wireless communications systems are considered. Joint detection methods are applied to combat the negative effects of the temporal and spatial interference. However, practical joint detectors are not commonly used due to their high complexity. Therefore, there is a constant need to deliver reduced complexity solutions that approach substantial fraction of the channel capacity. In the first part of this thesis it is shown that simple transmission technique employing repetition coding and interleaving combined with interference cancellation is an asymptotically optimal processing strategy when high interference is experienced, for instance due to the relatively high ratio of the number of signals to the number of orthogonal dimensions. Surprisingly, strong, capacity achieving codes exhibit inferior performance and are not well suited for iterative interference cancellation due to their sharp threshold characteristics. Motivated by this observation partitioned modulation is introduced and applied to a multiuser spread spectrum system, which inherently encompasses a repetition coding mechanism. The detection of the resulting signals employs a parallel interference cancellation approach, where the repetition code exchanges information iteratively with the canceller. Precise signal-to-noise ratio evolution of the proposed receiver as a function of demodulation iterations is given. It is shown, that for equal received power system, partitioned demodulator outperforms linear minimum mean squared error processor at a fraction of complexity. This receiver processing for a wide range of parameters delivers estimates that coincide with the optimal processing based on exhaustive search. For unequal received signal powers these advantages are even more visible and for a particular exponential power allocation the proposed system reaches the capacity of the channel. The analytical investigations are verified using computer simulations. In the second part of this dissertation, multi-user MIMO systems compliant with 3GPP LTE standard are considered. Turbo near-far resistant interference cancellation receiver is proposed. It jointly removes multi-user, multi-antenna and inter-symbol interference and outperforms traditional demodulation/decoding method adopted in the LTE standard. Semi-analytical method of predicting the performance of this joint receiver for any system setup is outlined. This approach makes it possible to tune up the performance of the system without running extensive bit-error-rate simulations. / Communications

Recent wireless communication research faces the challenge of meeting a predicted 1000x increase in demand for wireless Internet data over the next decade. Among the key reasons for such explosive increase in demand include the evolution of Internet as a provider of high-definition video entertainment and two-way video communication, accessed via mobile wireless devices. One way to meet some of this demand is by using multiple antennae at the transmitter and receiver in a wireless device. For example, a system with 4 transmit and 4 receive antennae can provide up to a 4x increase in data throughput. Another key aspect of the overall solution would require sharing radio frequency spectral resources among users, causing severe amounts of interference to wireless systems. Consequently, wireless receivers with multiple antennae would be deployed in network environments that are rife with interference primarily due to wireless resource sharing among users. Other significant sources of interference include computational platform subsystems, signal leakage, and external electronics. Interference causes severe degradation in communication performance of wireless receivers. Having accurate statistical models of interference is a key requirement to designing, and analyzing the communication performance of, multi-antenna wireless receivers in the presence of interference. Prior work on statistical modeling of interference in multi-antenna receivers utilizes either the Gaussian distribution, or non-Gaussian distributions exhibiting either statistical independence or spherical isotropy. This dissertation proposes a framework, based on underlying statistical-physical mechanism of interference generation and propagation, for modeling multi-antenna interference in various network topologies. This framework can model interference which is spherically isotropic, or statistically independent, or somewhere on a continuum between these two extremes. The dissertation then utilizes the derived statistical models to analyze communication performance of multi-antenna receivers in interference-limited wireless networks. Accurate communication performance analysis can highlight the tradeoffs between communication performance and computational complexity of various multi-antenna receiver designs. Finally, using interference statistics, this dissertation proposes receiver algorithms that best mitigate the impact of interference on communication performance. The proposed algorithms include multi-antenna combining strategies, as well as, antenna selection algorithms for cooperative communications. / text

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In this work, we make contributions in three main areas of Cognitive Engine (CE) design for link adaptation. The three areas are CE design, CE training, and the impact of imperfect observations in the operation of the CE. First, we present a CE design for link adaptation and apply it to a system which can adapt its use of multiple antennas in addition to modulation and coding. Our design moves forward the state of the art in several ways while having a simple structure. Specifically, the CE only needs to observe the number of successes and failures associated with each set of channel conditions and communication method. From these two numbers, the CE can derive all of its functionality: estimate confidence intervals, balance exploration vs. exploitation, and utilize prior knowledge such as communication fundamentals. Finally, the CE learns the radio abilities independently of the operation objectives. Thus, if an objective changes, information regarding the radio's abilities is not lost. Second, we provide an overview of CE training, and we analytically estimate the number of trials needed to conclusively find the best performing method in a list of methods sorted by their potential performance. Furthermore, we propose the Robust Training Algorithm (RoTA) for applications where stable performance is of topmost importance. Finally, we test four key training techniques and identify and explain the three main factors that affect performance during training. Third, we assess the impact of the estimation noise on the performance of a CE. Furthermore, we derive the effect of estimation delay, in terms of the correlation between the observed SNR and the true SNR. We evaluate the effect of estimation noise and delay to the operation of the CE individually and jointly. It is found that impairments on learning make the CE more conservative in its choices leading to submaximal performance. It is found that the CE should learn using the impaired observations, if the observations are highly correlated with the actual conditions. Otherwise, it is better for the CE to learn with knowledge of the ideal conditions, if that knowledge is available. / Ph. D.

This dissertation focuses on downlink multi-antenna transmission with packet scheduling in a wireless packet data network. The topic is viewed as a critical system design problem for future high-speed packet networks requiring extremely high spectral efficiency. Our aim is to illustrate the interaction between transmission schemes at the physical layer and scheduling algorithms at the medium access control (MAC) layer from a sum-capacity perspective. Various roles of multiple antennas are studied under channel-aware scheduling, including diversity, beamforming and spatial multiplexing. At a system performance level, our work shows that downlink throughput can be optimized by joint precoding across multiple transmit antennas and exploiting small-scale fading of distributed multiple input and multiple output (MIMO) channels. There are three major results in this dissertation. First, it is shown that over a MIMO Gaussian broadcast channel, and under channel-aware scheduling, open-loop transmit antenna diversity actually reduces the achievable sum rate. This reveals a negative interaction between open-loop antenna diversity and the closed-loop multiuser diversity through scheduling. Second, a suboptimal dirty paper coding (DPC) approach benefits greatly from multiuser diversity by an efficient packet scheduling algorithm. Performance analysis of a suboptimal greedy scheduling algorithm indicates that, compared with the receiver-centric V-BLAST method, it can achieve a much larger scheduling gain over a distributed MIMO channel. Further, pre-interference cancellation allows for transmissions free of error propagation. A practical solution, termed Tomlinson-Harashima precoding (THP), is studied under this suboptimal scheduling algorithm. Similar to V-BLAST, a reordering is applied to minimize the average error rate, which introduces only a negligible sum-rate loss in the scenarios investigated. Third, for an orthogonal frequency division multiplexing (OFDM) system using MIMO precoding, it is shown that a DPC-based approach is readily applicable and can be easily generalized to reduce the peak-to-average power ratio (PAR) up to 5 dB without affecting the receiver design. Simulations show that in an interference-limited multi-cell scenario, greater performance improvement can be achieved by interference avoidance through adaptive packet scheduling, rather than by interference diversity or averaging alone. These findings suggest that, coordinated with channel-aware scheduling, adaptive multiplexing in both spatial and frequency domains provides an attractive downlink solution from a total capacity point of view. / Ph. D.

This thesis presents new methodologies to improve performance of wireless cooperative networks using the Golden Code. As a form of space-time coding, the Golden Code can achieve diversity-multiplexing tradeoff and the data rate can be twice that of the Alamouti code. In practice, however, asynchronism between relay nodes may reduce performance and channel quality can be degraded from certain antennas. Firstly, a simple offset transmission scheme, which employs full interference cancellation (FIC) and orthogonal frequency division multiplexing (OFDM), is enhanced through the use of four relay nodes and receiver processing to mitigate asynchronism. Then, the potential reduction in diversity gain due to the dependent channel matrix elements in the distributed Golden Code transmission, and the rate penalty of multihop transmission, are mitigated by relay selection based on two-way transmission. The Golden Code is also implemented in an asynchronous one-way relay network over frequency flat and selective channels, and a simple approach to overcome asynchronism is proposed. In one-way communication with computationally efficient sphere decoding, the maximum of the channel parameter means is shown to achieve the best performance for the relay selection through bit error rate simulations. Secondly, to reduce the cost of hardware when multiple antennas are available in a cooperative network, multi-antenna selection is exploited. In this context, maximum-sum transmit antenna selection is proposed. End-to-end signal-to-noise ratio (SNR) is calculated and outage probability analysis is performed when the links are modelled as Rayleigh fading frequency flat channels. The numerical results support the analysis and for a MIMO system maximum-sum selection is shown to outperform maximum-minimum selection. Additionally, pairwise error probability (PEP) analysis is performed for maximum-sum transmit antenna selection with the Golden Code and the diversity order is obtained. Finally, with the assumption of fibre-connected multiple antennas with finite buffers, multiple-antenna selection is implemented on the basis of maximum-sum antenna selection. Frequency flat Rayleigh fading channels are assumed together with a decode and forward transmission scheme. Outage probability analysis is performed by exploiting the steady-state stationarity of a Markov Chain model.

Different techniques are being implemented in modern communication networks to ensure that their coverage, capacity, and other user-experience requirements are always met. In this thesis, I consider multi-antenna techniques, energy harvesting, and the dense deployment of small cell base stations in a two-tiered wireless powered communication network (WPCN) where multi-antenna transmitters utilize a Harvest Then Transmit (HTT) protocol to coordinate wireless energy harvesting and information transmission with their associated users. To satisfy network throughput requirements at all user positions, I formulate multi-constraint optimization problems to maximize the minimum data rate at both tier and network levels, solving the resulting non-convex expressions with an algorithm which incorporates the Perron-Frobenius non-negative matrix theory for alternate parameter optimization. I also present a less complex solution methodology, compared the performance of both and provided interesting insights on my findings. / October 2016

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / Devido ao rÃpido crescimento e os agressivos requisitos de vazÃo nas atuais redes sem fio, como os sistemas celulares de 4 a GeraÃÃo, a interferÃncia se tornou um problema que nÃo pode mais ser negligenciado. Neste contexto, o Alinhamento de InterferÃncia (IA) tem surgido como uma tÃcnica promissora que possibilita transmissÃes livres de interferÃncia com elevada eficiÃncia espectral. No entanto, trabalhos recentes tÃm focado principalmente nos ganhos teÃricos que esta tÃcnica pode prover, enquanto esta dissertaÃÃo visa dar um passo na direÃÃo de esclarecer alguns dos problemas prÃticos de implementaÃÃo da tÃcnica em redes celulares, bem como comparÃ-la com outras tÃcnicas bem estabelecidas. Uma rede composta por trÃs cÃlulas foi escolhida como cenÃrio inicial de avaliaÃÃo, para o qual diversos fatores realistas foram considerados de modo a realizar diferentes anÃlises. A primeira anÃlise foi baseada em imperfeiÃÃes de canal, cujos resultados mostraram que o IA à mais robusto aos erros de estimaÃÃo de canal que o BD (do inglÃs, Block Diagonalization), enquanto as duas abordagens sÃo igualmente afetadas pela correlaÃÃo entre as antenas. O impacto de uma interferÃncia externa nÃo-coordenada, que foi modelada por diferentes matrizes de covariÃncia de modo a emular vÃrios cenÃrios, tambÃm foi avaliado. Os resultados mostraram que as modificaÃÃes feitas nos algoritmos de IA podem melhorar bastante seus desempenho, com uma vantagem para o algoritmo que suprime um Ãnico fluxo de dados, quando sÃo comparadas as taxas de erro de bit alcanÃadas por cada um. Para combinar os fatores das anÃlises anteriores, as variaÃÃes temporais de canal foram consideradas. Neste conjunto de simulaÃÃes, alÃm da presenÃa da interferÃncia externa, os prÃ-codificadores sÃo calculados atravÃs de medidas atrasadas de canal, levando a resultados que corroboraram com as anÃlises anteriores. Um fato recorrente percebido em todas as anÃlises anteriores à o dilema entre aplicar os algoritmos baseados em BD, para que se consiga alcanÃar maiores capacidades, ou enviar a informaÃÃo atravÃs de um enlace mais confiÃvel utilizando o IA. Uma maneira de esclarecer este dilema à efetivamente realizar simulaÃÃes a nÃvel sistÃmico, para isto foi aplicado um simulador sistÃmico composto por um grande nÃmero de setores. Como resultado, todas as anÃlises realizadas neste simulador mostraram que a tÃcnica de IA atinge desempenhos intermediÃrios entre a nÃo cooperaÃÃo e os algoritmos baseados na prÃ-codificaÃÃo conjunta. Uma das principais contribuiÃÃes deste trabalho foi mostrar alguns cenÃrios em que a tÃcnica do IA pode ser aplicada. Por exemplo, quando as estimaÃÃes dos canais nÃo sÃo tÃo confiÃveis à melhor aplicar o IA do que os esquemas baseados no processamento conjunto. TambÃm mostrou-se que as modificaÃÃes nos algoritmos de IA, que levam em consideraÃÃo a interferÃncia externa, podem melhorar consideravelmente o desempenho dos algoritmos. Finalmente, o IA se mostrou uma tÃcnica adequada para ser aplicada em cenÃrios em que a interferÃncia à alta e nÃo à possÃvel ter um alto grau de cooperaÃÃo entre os setores vizinhos. / Due to the rapid growth and the aggressive throughput requirements of current wireless networks, such as the 4th Generation (4G) cellular systems, the interference has become an issue that cannot be neglected anymore. In this context, the Interference Alignment (IA) arises as a promising technique that enables transmissions free of interference with high-spectral efficiency. However, while recent works have focused mainly on the theoretical gains that the technique could provide, this dissertation aims to go a step further and clarify some of the practical issues on the implementation of this technique in a cellular network, as well as compare it to other well-established techniques. As an initial evaluation scenario, a 3-cell network was considered, for which several realistic factors were taken into account in order to perform different analyses. The first analysis was based on channel imperfections, for which the results showed that IA is more robust than Block Diagonalization (BD) regarding the Channel State Information (CSI) errors, but both are similarly affected by the correlation among transmit antennas. The impact of uncoordinated interference was also evaluated, by modeling this interference with different covariance matrices in order to mimic several scenarios. The results showed that modifications on the IA algorithms can boost their performance, with an advantage to the approach that suppresses one stream, when the Bit Error Rate (BER) is compared. To combine both factors, the temporal channel variations were taken into account. At these set of simulations, besides the presence of an external interference, the precoders were calculated using a delayed CSI, leading to results that corroborate with the previous analyses. A recurring fact on the herein considered analyses was the dilemma of weather to apply the Joint Processing (JP)-based algorithms in order to achieve higher sum capacities or to send the information through a more reliable link by using IA. A reasonable step towards solving this dilemma is to actually perform the packet transmissions, which was accomplished by employing a system-level simulator composed by a large number of Transmission Points (TPs). As a result, all analyses conducted with this simulator showed that the IA technique can provide an intermediate performance between the non-cooperation and the full cooperation scheme. Concluding, one of the main contributions of this work has been to show some scenarios/cases where the IA technique can be applied. For instance, when the CSI is not reliable it can be better to use IA than a JP-based scheme. Also, the modifications on the algorithms to take into account the external interference can boost their performance. Finally, the IA technique finds itself in-between the conventional transmissions and Coordinated Multi-Point (CoMP). IA achieves an intermediate performance, while requiring a certain degree of cooperation among the neighboring sectors, but demanding less infrastructure than the JP-based schemes.

This thesis explores a novel technique for transceiver design in future wireless systems, which is cloud radio access networks (CRANs) with single radio frequency (RF) chain antennas at each remote radio head (RRH). This thesis seeks to make three contributions. Firstly, it proposes a novel algorithm to solve the oscillatory/unstable behaviour of electronically steerable parasitic array radiators (ESPAR) when it provides multi-antenna functionality with a single RF chain. This thesis formulates an optimization problem and derives closed-form expressions when calculating the configuration of an ESPAR antenna (EA) for arbitrary signals transmission. This results in simplified processing at the transmitter. The results illustrate that the EA transmitter, when utilizing novel closed-form expressions, shows significant improvement over the performance of the EA transmitter without any pre-processing. It performs at nearly the same symbol error rate (SER) as standard multiple antenna systems. Secondly, this thesis illustrates how a practical peak power constraint can be put into an EA transceiver design. In an EA, all the antenna elements are fed centrally by a single power amplifier. This makes it more probable that during use, the power amplifier reaches maximum power during transmission. Considering limited power availability, this thesis proposes a new algorithm to achieve stable signal transmission. Thirdly, this thesis shows that an energy efficiency (EE) optimization problem can be formulated and solved in CRANs that deploy single RF chain antennas at RRHs. The closed-form expressions of the precoder and power allocation schemes to transmit desired signals are obtained to maximise EE for both single-user and multi-user systems. The results show that the CRANs with single RF chain antennas provide superior EE performance compared to the standard multiple antenna based systems.

Signal-scale cooperation is a class of techniques designed to harness the same gains offered by multi-antenna communication in scenarios where devices are too small to contain an array of antennas. While the potential improvements in reliability at the physical layer are well known, three key challenges must be addressed to harness these gains at the medium access layer: (a) the distributed synchronization and coordination of devices to enable cooperative behavior, (b) the conservation of energy for devices cooperating to help others, and (c) the management of increased inter-device interference caused by multiple spatially separate transmissions in a cooperative network. In this thesis, we offer three contributions that respectively answer the above three challenges. First, we present two novel cooperative medium access control protocols: Distributed On-demand Cooperation (DOC) and Power-controlled Distributed On-demand Cooperation (PDOC). These protocols utilize negative acknowledgments to synchronize and trigger cooperative relay transmissions in a completely distributed manner. Furthermore, they avoid cooperative transmissions that would likely be unhelpful to the source of the traffic. Second, we present an energy conservation algorithm known as Distributed Energy-Conserving Cooperation (DECC). DECC allows devices to alter their cooperative behavior based on measured changes to their own energy efficiency. With DECC, devices become self-aware of the impact of signal-scale cooperation -- they explicitly monitor their own performance and scale the degree to which they cooperate with others accordingly. Third and finally, we present a series of protocols to combat the challenge of inter-device interference. Whereas energy efficiency can be addressed by a self-aware device monitoring its own performance, inter-device interference requires devices with network awareness that understand the impact of their behavior on the devices around them. We investigate and quantify the impact of incomplete network awareness by proposing a modeling approximation to derive relaying policy behaviors. We then map these policies to protocols for wireless channels.