The next generation (4G) wireless systems are expected to provide universal personal and multimedia communications with seamless connection and very high rate transmissions and without regard to the users’ mobility and location. OFDM technique is recognized as one of the leading candidates to provide the wireless signalling for 4G systems. The major challenges in downlink multiuser OFDM based 4G systems include the wireless channel, the synchronization and radio resource management. Thus algorithms are required to achieve accurate timing and frequency offset estimation and the efficient utilization of radio resources such as subcarrier, bit and power allocation. The objectives of the thesis are of two fields. Firstly, we presented the frequency offset estimation algorithms for OFDM systems. Building our work upon the classic single user OFDM architecture, we proposed two FFT-based frequency offset estimation algorithms with low computational complexity. The computer simulation results and comparisons show that the proposed algorithms provide smaller error variance than previous well-known algorithm. Secondly, we presented the resource allocation algorithms for OFDM systems. Building our work upon the downlink multiuser OFDM architecture, we aimed to minimize the total transmit power by exploiting the system diversity through the management of subcarrier allocation, adaptive modulation and power allocation. Particularly, we focused on the dynamic resource allocation algorithms for multiuser OFDM system and multiuser MIMO-OFDM system. For the multiuser OFDM system, we proposed a lowiv complexity channel gain difference based subcarrier allocation algorithm. For the multiuser MIMO-OFDM system, we proposed a unit-power based subcarrier allocation algorithm. These proposed algorithms are all combined with the optimal bit allocation algorithm to achieve the minimal total transmit power. The numerical results and comparisons with various conventional nonadaptive and adaptive algorithmic approaches are provided to show that the proposed resource allocation algorithms improve the system efficiencies and performance given that the Quality of Service (QoS) for each user is guaranteed. The simulation work of this project is based on hand written codes in the platform of the MATLAB R2007b.

This thesis investigates optimization of advanced telecommunication algorithms from power and performance perspectives. The algorithms chosen are MIMO and LDPC. MIMO is implemented in custom ASIC for power optimization and LDPC is implemented on dynamically reconfigurable fabric for both power and performance optimization. Both MIMO and LDPC are considered computational bottlenecks of current and future wireless standards such as IEEE 802.11n for Wi-Fi and IEEE 802.16 for WiMax applications. Optimization of these algorithms is carried out separately. The thesis is organized implicitly in two parts. The first part presents selection and analysis of the VBLAST receiver used in MIMO wireless system from custom ASIC perspective and identifies those processing elements that consume larger area as well as power due to complex signal processing. The thesis models a scalable VBLAST architecture based on MMSE nulling criteria assuming block rayleigh flat fading channel. After identifying the major area and power consuming blocks, it proposes low power and area efficient VLSI architectures for the three building blocks of VBLAST namely Pseudo Inverse, Sorting and NULLing & Cancellation modules assuming a 4x4 MIMO system. The thesis applies dynamic power management, algebraic transformation (strength reduction), resource sharing, clock gating, algorithmic modification, operation substitution, redundant arithmetic and bus encoding as the low power techniques applied at different levels of design abstraction ranging from system to architecture, to reduce power consumption. It also presents novel architectures not only for the constituent blocks but also for the whole receiver. It builds the low power VBLAST receiver for single carrier and provides its area, power and performance figures. It then investigates into the practicality and feasibility of VBLAST into an OFDM environment. It provides estimated data with respect to silicon real estate and throughput from which conclusion can easily be drawn about the feasibility of VBLAST in a multi carrier environment. The second part of the thesis presents novel architectures for the real time adaptive LDPC encoder and decoder as specified in IEEE 802.16E standard for WiMax application. It also presents optimizations of encoder as well as decoder on RICA (Reconfigurable Instruction Cell Architecture). It has searched an optimized way of storing the H matrices that reduces the memory by 20 times. It uses Loop unrolling to distribute the instructions spatially depending upon the available resources to execute them concurrently to as much as possible. The parallel memory banks and distributed registers inside RICA allow good reduction in memory access time. This together with hardware pipelining provides substantial potential for optimizing algorithms from power and performance perspectives. The thesis also suggests ways of improvements inside RICA architecture.

In this dissertation, channel modeling for Terahertz (THz) channels and designs of nano devices for THz communications are studied. THz communication becomes more and more important for future wireless communication systems that require an ultra high data rate, which motivates us to propose new nano device designs based on graphene and new system models for the THz channel. Besides, the multiple-input multiple-output (MIMO) antenna technique is well known to increase the spectral efficiency of a wireless communications system. Considering THz channels' particular characteristics, MIMO systems with reconfigurable antennas and distributed antennas are proposed. We compare the differences between MIMO systems in the GHz and THz bands, and highlight the benefits of using multi antennas in the THz band. The work on nano device designs provides two antenna designs with single walled carbon nanotubes (SWCNTs) and graphene nano ribbon (GNR). First, we analyse the spectral efficiency of an SWCNT bundled dipole antenna based MIMO system in the Terahertz band. Two scenarios are considered: the large scale MIMO and the conventional scale MIMO. It is found that, in order to get the maximum spectral efficiency, the CNT bundle size should be optimized to obtain a tradeoff between the antenna efficiency and the number of antennas for a given area. We also discuss the random fluctuation in the bundle size during the CNT bundled antenna fabrication which reduces the system spectral efficiency. Then, we propose reconfigurable directional antennas for THz communications. The beamwidth and direction can be controlled by the states of each graphene patch in the antenna, and the states can be easily configured by changing the electrostatic bias voltage on each element. The work on reconfigurable MIMO system proposes a new antenna array design for MIMO in the THz band. First, the path loss and reflection models of the THz channel are discussed. Then, we combine the graphene-based antenna and the THz channel model and propose a new MIMO antenna design. The radiation directions of the transmit antennas can be programmed dynamically, leading to different channel state matrices. Finally, the path loss and the channel capacity are numerically calculated and compared with those of the GHz channel. The results show that for short range communications, the proposed MIMO antenna design can enlarge the channel capacity by both increasing the number of antennas and choosing the best channel state matrices. The work on MIMO channels proposes a statistical model for the MIMO channel with rough reflection surfaces in the THz Band. First, our analysis of scattering from a rough surface indicates that the reflection from a single surface can be a cluster of rays. Secondly, a new MIMO model for THz communications is proposed. In this model, the number of multipaths is highly dependent on the roughness of the reflecting surfaces. When the surface is ideally smooth, the MIMO channel is sparse and as a result, the capacity is sub-linear with the MIMO scale. On the other hand, when the surface is rough, more degrees of freedom are provided by the scattered rays. Finally, channel capacities with different surface roughness are numerically calculated and compared between different MIMO scales. The results show that in contrast to the GHz range, large scale THz multiple antennas may not provide as much multiplexing gain. Therefore, it is necessary to determine the antenna scale according to the actual propagation environment. The work on distributed antenna systems (DAS) proposes a new DAS model in the THz band. First, the model of DAS in the THz frequency is discussed, which has fewer multipaths than that in the GHz band. Then, we analyze the characteristics of the DAS model and point out that the channel is very sparse if the number of antennas on the base station (BS) is very large. Besides, we provide reasons for the fact that DAS can have a large number of degrees of freedom. We compare the capacities of MIMO systems with DAS and without DAS. The results show that for THz channels, increasing the number of antenna units (AUs) is much more important than increasing the number of antennas in one AU. Finally, we propose an antenna selection and precoding scheme which has very low complexity. / Graduate

The past decade has shown distinct advances in the theory of multiple input multi output techniques for wireless communication systems. Now, the time has come to demonstrate this progress in terms of applications. This thesis introduces implementation of Schnorr- Euchner strategy based decoding algorithm applied on Altera system-on-chip (Stratix EP1S10F780C6) with Nios embedded processor. The lattice decoder is developed on FPGA using VHDL. The preprocessing part of algorithm is targeted for Nios embedded processor using C language. A controller is also designed to interface and communicate between the Nios embedded processor and lattice decoder.

Multiple-input multiple-output (MIMO) technique in communication system has been widely researched. Compared with single-input single-output (SISO) communication, its properties of higher throughput, more e?cient spectrum and usage make it one of the most significant technology in modern wireless communications. In MIMO system, sphere detection is the fundamental part. The purpose of traditional sphere detection is to achieve the maximum likelihood (ML) demodulation of the MIMO system. However, with the development of advanced forward error correction (FEC) techniques, such as the Convolutional code, Turbo code and LDPC code, the sphere detection algorithms that can provide soft information for the outer decoder attract more interests recently. Considering the computing complexity of generating the soft information, it is important to develop a high-speed VLSI architecture for MIMO detection. The first part of this thesis is about MIMO sphere detection algorithms. Two sphere detection algorithms are introduced. The depth first Schnorr-Euchner (SE) algorithm which generates the ML detection solution and the width first K-BEST algorithm which only generates the nearly-ML detection solution but more efficient in implementation are presented. Based on these algorithms, an improved nearly-ML algorithm with lower complexity and limited performance lose, compared with traditional K-BEST algorithms, is presented. The second part is focused on the hardware design. A 4*4 16-QAM MIMO detection system which can generate both soft information and hard decision solution is designed and implemented in FPGA. With the fully pipelined and parallel structure, it can achieve a throughput of 3.7 Gbps. In this part, the improved nearly-ML algorithm is implmented as a detector to generat both the hard output and candidate list. Then, a soft information calculation block is designed to succeed the detector and produce the log-likelihood ratio (LLR) values for every bit as the soft output.

多輸入多輸出傳輸在過去二十多年來無線通信研究中一直處於中心地位。人們對信息需求的爆炸性增長導致大規模多輸入多輸出系統的出現與發展。在大規模多輸入多輸出系統中有幾十甚至上百的天線與用戶。這種大規模天線能夠極大地提高系統容量及對噪聲的魯棒性。然而，大規模天線系統的物理實現卻是十分困難的。一方面，最優的信號處理算法通常需要指數增長的複雜度。另一方面，數目繁多的天線意味大量包括功率放大器和數模轉換器在內的硬件開銷。這篇論文的研究重點在於能夠降低信號處理複雜度和硬件開銷的信號檢測和預編碼算法。具體而言，本論文的研究包括三部分： / 在第一部分中，我們考慮多輸入多輸出系統中的一個基本問題信號檢測。格型解碼是信號檢測中的一種傳統方法。但是格型解碼（以及其快速近似算法格基規約輔助算法)放鬆了信號檢測中的符號邊界約束因而受到性能限制。我們提出一種自適應的正則化方法來避免格型解碼中邊界約束鬆弛帶來的負面影響。這種方法是基於最大似然解碼器的拉格朗日對偶鬆弛。我們發現了格型解碼和最大似然解碼的一個十分有趣的關係，而這個關係在現有的文獻中並沒有被提及。數值仿真結果顯示拉格朗日對偶鬆弛方法比現有的格型解碼更為優勝。 / 在第二部分中，我們考慮多用戶信號廣播中的矢量擾動方法。矢量擾動是一種能夠接近信道總容量以及簡化用戶數據處理方法。然而，傳統的矢量擾動會導致每根傳輸天線上都有相當大的功率， 導致天線模擬前端的硬件實現有相當大的難度。我們提出一種每天線功率受限的矢量擾動方法來解決這個問題。在這個方法中，我們需要解決一個整數規劃問題。然而，求解這個整數規劃問題需要用到複雜度十分高的枚舉算法。我們用拉格朗日對偶鬆弛方法把這個整數規劃轉化為標準的整數最小二乘問題，然後採用快速的近似算法來求解。數值仿真顯示提出的方法能夠顯著地降低高每天線功率造成的功率回饋。 / 在最後一部分，我們考慮單用戶通信中的恆定包絡預編碼。恆定包絡預編碼是一種最近被提出用於超大規模多輸入多輸出系統的方法。恆定包絡預編碼的優點在於能夠利用價格低廉但是功率效率高的功率放大器。但是恆定包絡預編碼中的一些信號處理問題在之前的文獻中只是得到了部分解答。我們為這些信號處理問題提供了一個完整的解決方案。更進一步地，我們用天線子集選擇來加強恆定包絡預編碼以優化天線傳輸信號及進一步降低天線成本。數值仿真結果顯示包絡預編碼的性能只稍遜於傳統的波束成型方法，但是能恆定包絡傳輸和降低活動的天線數目。 / Multiple-input multiple-output (MIMO) transmission has been at the core of wireless communication research for the past two decades. Driven by the explosive increase of data demand, the development of MIMO systems has entered a large-scale realm where there are dozens of or even more than a hundred antennas and users. The large number of antennas can significantly boost the system throughput and robustness against noise. However, the physical realization of such a large MIMO system can be very complicated and expensive. On the one hand, optimal signal processing algorithms usually have complexities that increase rapidly in the numbers of antennas and users. On the other hand, large number of antennas means increased hardware overheads, such as those of power amplifiers and D/A converters. This thesis considers efficient precoding and detection algorithms that can reduce implementation complexity and cost. Specifically, the thesis consists of the following three parts: / In the first part, we consider a fundamental problem in MIMO communication, namely MIMO detection. The traditional lattice decoding methods, as well as its efficient approximations by lattice reduction aided (LRA) methods, relax the symbol bounds in detection and thus suffer from performance loss. We propose a systematic adaptive regularization approach to lattice decoding to alleviate the adverse effect of symbol bound relaxation, which is based on the study of a Lagrangian dual relaxation (LDR) of the optimal maximum-likelihood (ML) detector. We find an intriguing relationship between lattice decoding and ML, which was not reported in the previous literature. Simulation results show that the proposed LDR approach can significantly outperform existing lattice decoding and LRA methods. / In the second part, we consider the vector perturbation approach which is a promising technique to achieve near-sum capacity and allows simple user processing in the multiuser multiple-input single-output (MISO) downlink scenario. However, the conventional vector perturbation designs can have very high perantenna powers, which causes significant difficulty to power amplifier implementations. To tackle this problem, we propose a vector perturbation design with per-antenna power constraints (VP-PAPC). The resulting optimization problem is an integer program which requires a computationally demanding enumeration process. Lagrangian dual relaxation is used to transform the VP-PAPC problem into standard integer least square problems which may have efficient approximations. Simulation results show that the proposed method can effectively reduce the power back-off caused by high per-antenna power in conventional vector perturbation. / In the last part, we consider constant envelope (CE) precoding in the singleuser MISO downlink scenario. CE precoding is recently proposed as a mean to utilize cheap but power-efficient power amplifiers in very large MIMO systems. We provide complete solutions to some fundamental signal processing issues in CE precoding which were only partially solved in the previous literature. In addition, we enhance CE precoding with antenna subset selection for transmit optimization and implementation cost reduction. Simulation results reveal that the proposed method only exhibits moderate power loss compared to non-CE beamforming but have the advantages of CE transmission and fewer active transmitting antennas. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Pan, Jiaxian. / Thesis (Ph.D.) Chinese University of Hong Kong, 2014. / Includes bibliographical references (leaves 135-147). / Abstracts also in Chinese.

In this thesis, we analyze the performance of three promising technologies being considered for future fifth generation (5G) and beyond wireless communication systems, with primary goals to: i) render 10-100 times higher user data rate, ii) serve 10-100 times more users simultaneously, iii) 1000 times more data volume per unit area, iv) improve energy efficiency on the order of 100 times, and iv) provide higher bandwidths. Accordingly, we focus on massive multiple-input multiple-output (MIMO) systems and other future wireless technologies, namely millimeter wave (mmWave) and full-duplex (FD) systems that are being considered to fulfill the above requirements. We begin by focusing on fundamental performance limits of massive MIMO systems under practical constraints such as low complexity processing, array size and limited physical space. First, we analyze the performance of a massive MIMO base station (BS) serving spatially distributed multi-antenna users within a fixed coverage area. Stochastic geometry is used to characterize the spatially distributed users while large dimensional random matrix theory is used to achieve deterministic approximations of the sum rate of the system. We then examine the deployment of a massive MIMO BS and the resulting energy efficiency (EE) by considering a more realistic set-up of a rectangular array with increasing antenna elements within a fixed physical space. The effects of mutual coupling and correlation among the BS antennas are incorporated by deriving a practical mutual coupling matrix which considers coupling among all antenna elements within the BS. Accordingly, the optimum number of antennas that can be deployed for a particular antenna spacing when EE is considered as a design criteria is derived. Also, it is found that mutual coupling effect reduces the EE of the massive system by around 40-45% depending on the precoder/receiver used and the physical space available for antenna deployment. After establishing the constraints of antenna spacing on massive MIMO systems for the current microwave spectrum, we shift our focus to mmWave frequencies (more than 100GHz available bandwidth), where the wavelength is very small and as a result more antennas can be rigged within a constrained space. Accordingly, we integrate the massive MIMO technology with mmWave networks. In particular, we analyze the performance of a mmWave network consisting of spatially distributed BS equipped with very large uniform circular arrays (UCA) serving spatially distributed users within a fixed coverage area. The use of UCA is due to its capability of scanning through both the azimuth as well as elevation dimensions. We show that using such 3D massive MIMO techniques in mmWave systems yield significant performance gains. Further, we show the effect of blockages and path loss on mmWave networks. Since blockages are found to be quite detrimental to mmWave networks, we create alternative propagation paths with the aid of relays. In particular, we consider the deployment of relays in outdoor mmWave networks and then derive expressions for the coverage probability and transmission capacity from sources to a destination for such relay aided mmWave networks using stochastic geometric tools. Overall, relay aided mmWave transmission is seen to improve the signal to noise ratio at the destination by around 5-10dB with respect to specific coverage probabilities. Finally, due to the fact that the current half duplex (HD) mode transmission only utilizes half the spectrum at the same time in the same frequency, we consider a multiuser MIMO cellular system, where a FD BS serves multiple HD users simultaneously. However, since FD systems are plagued by severe self-interference (SI), we focus on the design of robust transceivers, which can cancel the residual SI left after antenna and analog cancellations. In particular, we address the sum mean-squared-errors (MSE) minimization problem by transforming it into an equivalent semidefinite programming (SDP) problem. We propose iterative alternating algorithms to design the transceiver matrices jointly and accordingly show the gains of FD over HD systems. We show that with proper SI cancellation, it is possible to achieve gains on sum rate of up to 70-80% over HD systems.

FundaÃÃo de Amparo à Pesquisa do Estado do Cearà / Atualmente a internet à uma ferramenta largamente utilizada e o grande desenvolvimentoe popularidade de tecnologias de acesso sem-fio (wireless) nos levam a um futuro no qual uma conexÃo caracterizada por estar disponÃvel âanytime, anywhereâ, ou seja, a qualquer hora e em qualquer lugar, serà essencial. Tal caracterÃstica à considerada obrigatÃria em sistemas4G (quarta geraÃÃo), mas para uma experiÃncia satisfatÃria para o usuÃrio à necessÃrio que uma conexÃo segura e eficiente esteja disponÃvel. A fim de obter tal eficiÃncia, a comunidade de pesquisa tem gerado algumas soluÃÃes promissoras que obtÃm ganhos significativos no desempenho do sistema, tais como modulaÃÃo e codificaÃÃo adaptativas, codificaÃÃo espaÃo-temporal, mÃltiplas antenas e canais MIMO (Multiple Input Multiple Output ), modulaÃÃo multiportadora, detecÃÃo multiusuÃrio, etc. [1]. Dentre essas soluÃÃes, destaca-se a adaptaÃÃo do sistema, ou seja, o sistema deve estar em constante adaptaÃÃo para obter sempre o melhor desempenho possÃvel para cada situaÃÃo em que se encontra. No entanto, uma importante premissa para a adaptaÃÃo do sistema consiste em conhecer o estado atual em que o sistema se encontra (informaÃÃo sobre o canal de comunicaÃÃo). Para isso diversas tÃcnicas de estimaÃÃo de canal sÃo propostas na literatura, cada uma possuindo vantagens e desvantagens. Nesse trabalho o impacto da estimaÃÃo de canal na adaptaÃÃo de enlace à analisado atravÃs de simulaÃÃes computacionais1. Em particular, duas tÃcnicas de estimaÃÃo de canal com caracterÃsticas diferentes sÃo analisadas, para alguns cenÃrios especÃficos em um sistema MIMO-OFDM (Multiple Input Multiple Output - Orthogonal Frequency Division Multiplexing ), atravÃs de uma mÃtrica que considera tanto a redundÃncia introduzida para estimar o canal quanto o erro de estimaÃÃo de canal de cada tÃcnica. Os resultados encontrados constituem curvas que podem ser utilizadas para efetuar a adaptaÃÃo de enlace do sistema de maneira mais realista, ou seja, considerando o efeito da estimaÃÃo de canal, alÃm de incluir a prÃpria tÃcnica de estimaÃÃo de canal como um parÃmetro a ser adaptado. / Atualmente a internet à uma ferramenta largamente utilizada e o grande desenvolvimentoe popularidade de tecnologias de acesso sem-fio (wireless) nos levam a um futuro no qual uma conexÃo caracterizada por estar disponÃvel âanytime, anywhereâ, ou seja, a qualquer hora e em qualquer lugar, serà essencial. Tal caracterÃstica à considerada obrigatÃria em sistemas4G (quarta geraÃÃo), mas para uma experiÃncia satisfatÃria para o usuÃrio à necessÃrio que uma conexÃo segura e eficiente esteja disponÃvel. A fim de obter tal eficiÃncia, a comunidade de pesquisa tem gerado algumas soluÃÃes promissoras que obtÃm ganhos significativos no desempenho do sistema, tais como modulaÃÃo e codificaÃÃo adaptativas, codificaÃÃo espaÃo-temporal, mÃltiplas antenas e canais MIMO (Multiple Input Multiple Output ), modulaÃÃo multiportadora, detecÃÃo multiusuÃrio, etc. [1]. Dentre essas soluÃÃes, destaca-se a adaptaÃÃo do sistema, ou seja, o sistema deve estar em constante adaptaÃÃo para obter sempre o melhor desempenho possÃvel para cada situaÃÃo em que se encontra. No entanto, uma importante premissa para a adaptaÃÃo do sistema consiste em conhecer o estado atual em que o sistema se encontra (informaÃÃo sobre o canal de comunicaÃÃo). Para isso diversas tÃcnicas de estimaÃÃo de canal sÃo propostas na literatura, cada uma possuindo vantagens e desvantagens. Nesse trabalho o impacto da estimaÃÃo de canal na adaptaÃÃo de enlace à analisado atravÃs de simulaÃÃes computacionais1. Em particular, duas tÃcnicas de estimaÃÃo de canal com caracterÃsticas diferentes sÃo analisadas, para alguns cenÃrios especÃficos em um sistema MIMO-OFDM (Multiple Input Multiple Output - Orthogonal Frequency Division Multiplexing ), atravÃs de uma mÃtrica que considera tanto a redundÃncia introduzida para estimar o canal quanto o erro de estimaÃÃo de canal de cada tÃcnica. Os resultados encontrados constituem curvas que podem ser utilizadas para efetuar a adaptaÃÃo de enlace do sistema de maneira mais realista, ou seja, considerando o efeito da estimaÃÃo de canal, alÃm de incluir a prÃpria tÃcnica de estimaÃÃo de canal como um parÃmetro a ser adaptado. / Nowadays the internet is a widely used tool and the great development and popularity of wireless technologies leads us to a future where the connectivity will be characterized as âanywhere, anytimeâ. Such characteristic is considered essential in 4G systems. However, for a satisfactory user experience a secure and efficient connectivity has to be always available. To obtain such efficiency, the research community has generated a number of promising solutions that achieve significative improvements in system performance, such as adaptive modulation and coding, space-time coding, multiple antennas and MIMO (Multiple Input Multiple Output ) channels, multicarrier modulation, multiuser detection, etc. [1]. Among these solutions, the system adaptation is a particularly interesting one, there is, the system must constantly adapt itself to achieve the best performance for each situation. However, one important premise for the system adaptation is the knowledge of the channel state information (CSI). To obtain this knowledge, several channel estimation strategies were proposed in the literature, each one with advantages and disadvantages. In this work we analyze the impact of channel estimation in the link adaptation through computer simulations1. Two channel estimation techniques with different characteristics were analyzed for some specific scenarios in a MIMO-OFDM (Multiple Input Multiple Output - Orthogonal Frequency Division Multiplexing ) system. To perform the analysis it was used a metric that consider the redundancy introduced to estimate the channel and the channel estimation error of each technique. The obtained results constitute curves that can be used to perform link adaptation in a more realistic way, that is, considering the effect of channel estimation. Besides, it is shown that even the choice of the channel estimation strategy can be an adaptable parameter so that the most adequate channel estimation strategy for each system state is used. / Nowadays the internet is a widely used tool and the great development and popularity of wireless technologies leads us to a future where the connectivity will be characterized as âanywhere, anytimeâ. Such characteristic is considered essential in 4G systems. However, for a satisfactory user experience a secure and efficient connectivity has to be always available. To obtain such efficiency, the research community has generated a number of promising solutions that achieve significative improvements in system performance, such as adaptive modulation and coding, space-time coding, multiple antennas and MIMO (Multiple Input Multiple Output ) channels, multicarrier modulation, multiuser detection, etc. [1]. Among these solutions, the system adaptation is a particularly interesting one, there is, the system must constantly adapt itself to achieve the best performance for each situation. However, one important premise for the system adaptation is the knowledge of the channel state information (CSI). To obtain this knowledge, several channel estimation strategies were proposed in the literature, each one with advantages and disadvantages. In this work we analyze the impact of channel estimation in the link adaptation through computer simulations1. Two channel estimation techniques with different characteristics were analyzed for some specific scenarios in a MIMO-OFDM (Multiple Input Multiple Output - Orthogonal Frequency Division Multiplexing ) system. To perform the analysis it was used a metric that consider the redundancy introduced to estimate the channel and the channel estimation error of each technique. The obtained results constitute curves that can be used to perform link adaptation in a more realistic way, that is, considering the effect of channel estimation. Besides, it is shown that even the choice of the channel estimation strategy can be an adaptable parameter so that the most adequate channel estimation strategy for each system state is used.

Master of Engineering by Research / As a multi-carrier modulation scheme, Orthogonal Frequency Division Multiplexing (OFDM) technique can achieve high data rate in frequency-selective fading channels by splitting a broadband signal into a number of narrowband signals over a number of subcarriers, where each subcarrier is more robust to multipath. The wireless communication system with multiple antennas at both the transmitter and receiver, known as multiple-input multiple-output (MIMO) system, achieves high capacity by transmitting independent information over different antennas simultaneously. The combination of OFDM with multiple antennas has been considered as one of most promising techniques for future wireless communication systems. The challenge in the detection of a space-time signal is to design a low-complexity detector, which can efficiently remove interference resulted from channel variations and approach the interference-free bound. The application of iterative parallel interference canceller (PIC) with joint detection and decoding has been a promising approach. However, the decision statistics of a linear PIC is biased toward the decision boundary after the first cancellation stage. In this thesis, we employ an iterative receiver with a decoder metric, which considerably reduces the bias effect in the second iteration, which is critical for the performance of the iterative algorithm. Channel state information is required in a MIMO-OFDM system signal detection at the receiver. Its accuracy directly affects the overall performance of MIMO-OFDM systems. In order to estimate the channel in high-delay-spread environments, pilot symbols should be inserted among subcarriers before transmission. To estimate the channel over all the subcarriers, various types of interpolators can be used. In this thesis, a linear interpolator and a trigonometric interpolator are compared. Then we propose a new interpolator called the multi-tap method, which has a much better system performance. In MIMO-OFDM systems, the time-varying fading channels can destroy the orthogonality of subcarriers. This causes serious intercarrier interference (ICI), thus leading to significant system performance degradation, which becomes more severe as the normalized Doppler frequency increases. In this thesis, we propose a low-complexity iterative receiver with joint frequency- domain ICI cancellation and pilot-assisted channel estimation to minimize the effect of time-varying fading channels. At the first stage of receiver, the interference between adjacent subcarriers is subtracted from received OFDM symbols. The parallel interference cancellation detection with decision statistics combining (DSC) is then performed to suppress the interference from other antennas. By restricting the interference to a limited number of neighboring subcarriers, the computational complexity of the proposed receiver can be significantly reduced. In order to construct the time variant channel matrix in the frequency domain, channel estimation is required. However, an accurate estimation requiring complete knowledge of channel time variations for each block, cannot be obtained. For time- varying frequency-selective fading channels, the placement of pilot tones also has a significant impact on the quality of the channel estimates. Under the assumption that channel variations can be approximated by a linear model, we can derive channel state information (CSI) in the frequency domain and estimate time-domain channel parameters. In this thesis, an iterative low-complexity channel estimation method is proposed to improve the system performance. Pilot symbols are inserted in the transmitted OFDM symbols to mitigate the effect of ICI and the channel estimates are used to update the results of both the frequency domain equalizer and the PICDSC detector in each iteration. The complexity of this algorithm can be reduced because the matrices are precalculated and stored in the receiver when the placement of pilots symbols is fixed in OFDM symbols before transmission. Finally, simulation results show that the proposed MIMO-OFDM iterative receiver can effectively mitigate the effect of ICI and approach the ICI-free performance over time-varying frequency-selective fading channels.

In today's climate of increased criminal attacks on the privacy of personal or confidential data over digital communication systems, a more secure physical communication link is required. Chaotic signals which have bifurcation behavior (depending on some initial condition) can readily be exploited to enhance the security of communication systems. A chaotic generator produces disordered sequences that provide very good auto- and cross- correlation properties similar to those of random white noise. This would be an important feature in multiple access environments. These sequences are used to scramble data in spread spectrum systems as they can produce low co-channel interference, hence improve the system capacity and performance. The chaotic signal can be created from only a single mathematical relationship and is neither restricted in length nor is repetitive/ cyclic. On the other hand, with the progress in digital signal processing and digital hardware, there has been an increased interest in using adaptive algorithms to improve the performance of digital systems. Adaptive algorithms provide the system with the ability to self-adjust its coefficients according to the signal condition, and can be used with linear or non-linear systems; hence, they might find application in chaos communication. There has been a lot of literature that proposed the use of LMS adaptive algorithm in the communication arena for a variety of applications such as (but not limited to): channel estimation, channel equalization, demodulation, de-noising, and beamforming. In this thesis, we conducted a study on the application of chaos theory in communication systems as well as the application of adaptive algorithms in chaos communication. The First Part of the thesis tackled the application of chaos theory in com- munication. We examined different types of communication techniques utilizing chaos theory. In particular, we considered chaos shift keying (CSK) and mod- ified kind of logistic map. Then, we applied space-time processing and eigen- beamforming technique to enhance the performance of chaos communication. Following on, we conducted a study on CSK and Chaos-CDMA in conjunction with multi-carrier modulation (MCM) techniques such as OFDM (FFT/ IFFT) and wavelet-OFDM. In the Second Part of the thesis, we tried to apply adaptivity to chaos com- munication. Initially, we presented a study of multi-user detection utilizing an adaptive algorithm in a chaotic CDMA multi-user environment, followed by a study of adaptive beamforming and modified weight-vector adaptive beam- forming over CSK communication. At last, a study of modified time-varying adaptive filtering is presented and a conventional adaptive filtering technique is applied in chaotic signal environment. Twelve papers have been published during the PhD candidature, include two journal papers and ten refereed conference papers.