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The optimum ordering strategies for the coded V-BLAST system with capacity achieving temporal codes on each stream are studied in this thesis. Mathematical representations of the optimum detection ordering strategies for the coded V-BLAST under instantaneous rate allocation (IRA), uniform power/rate allocation (URA), instantaneous power allocation(IPA) and instantaneous power/rate allocation (IPRA) are derived. For two transmit antennas, it is shown that the optimum detection strategies are based on the per-stream before-processing channel gains. Based on approximations of the per-stream capacity equation, closed-form expressions of the optimal ordering strategy under the IRA at low and high signal to noise ratio (SNR) are derived. Necessary optimality conditions under the IRA are given. Thresholds for the low, intermediate and high SNR regimes in the 2-Tx-antenna system under the IPRA are determined, and the SNR gain of the ordering is studied for each regime. Performances of simple suboptimal ordering strategies are analysed, some of which perform very close to the optimum one.

We consider a variety of types of vertex sequences, which are defined in terms of a requirement that the next vertex in the sequence must meet. For example, let S = (v1, v2, …, vk ) be a sequence of distinct vertices in a graph G such that every vertex vi in S dominates at least one vertex in V that is not dominated by any of the vertices preceding it in the sequence S. Such a sequence of maximal length is called a dominating sequence since the set {v1, v2, …, vk } must be a dominating set of G. In this paper we survey the literature on dominating and other related sequences, and propose for future study several new types of vertex sequences, which suggest the beginning of a theory of vertex sequences in graphs.

As the world becomes more globalised, user equipment such as smartphones and Internet of Things devices require increasingly more data, which increases the demand for wireless data traffic. Hence, the acceleration of next-generational networks (5G and beyond) focuses mainly on increasing the bitrate and decreasing the latency. A crucial technology for 5G and beyond is the massive MIMO. In a massive MIMO system, a detector processes the received signals from multiple antennas to decode the transmitted data and extract useful information. This has been implemented in many ways, and one of the most used algorithms is the Zero Forcing (ZF) algorithm. This thesis presents a novel parallel design to accelerate the ZF algorithm using the Cholesky decomposition. This is implemented on a GPU, written in the CUDA programming language, and compared to the existing state-of-the-art implementations regarding latency and throughput. The implementation is also validated from a MATLAB implementation. This research demonstrates promising performance using GPUs for massive MIMO detection algorithms. Our approach achieves a significant speedup factor of 350 in comparison to a serial version of the implementation. The throughput achieved is 160 times greater than a comparable GPU-based approach. Despite this, our approach reaches a 2.4 times lower throughput than a solution that employed application-specific hardware. Given the promising results, we advocate for continued research in this area to further optimise detection algorithms and enhance their performance on GPUs, to potentially achieve even higher throughput and lower latency. / <p>Our examiner Mahdi wants to wait six months before the thesis is published. </p>

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / Este trabalho apresenta estudos sobre sistemas de comunicaÃÃo cujos sinais utilizados para a transmissÃo das informaÃÃes sÃo nÃo-ortogonais, superpostos em frequÃncia, e com espaÃamento entre portadoras menor do que a taxa de sÃmbolo. As pesquisas estÃo direcionadas na obtenÃÃo de estruturas de transmissor e receptor Ãtimos e sub-Ãtimos, na modelagem e anÃlise matemÃtica dos sistemas incluindo o canal, em propostas de estratÃgias para detecÃÃo de sÃmbolo, e na avaliaÃÃo de desempenho. SÃo propostas sete estratÃgias de recepÃÃo de N sinais m-QAM nÃo-ortogonais atravÃs do canal AWGN. Dentre as estratÃgias de detecÃÃo duas sÃo Ãtimas e as outras cinco sÃo subÃtimas. As duas estruturas de receptores Ãtimos apresentados neste trabalho sÃo: o receptor de mÃxima verossimilhanÃa (ML) clÃssico e o receptor de mÃxima verossimilhanÃa com base na decomposiÃÃo de Gram-Schmidt. Os receptores sub-Ãtimos desenvolvidos neste trabalho sÃo de dois tipos: receptores com equalizaÃÃo linear e receptores com equalizaÃÃo nÃo-linear. O primeiro tipo de receptor à desenvolvido com base nos critÃrios de erro quadrÃtico mÃdio mÃnimo (MMSE) e o de forÃagem a zero (ZF). à apresentado o desenvolvimento analÃtico do projeto de cada uma das arquiteturas de receptores lineares, assim como à determinado o erro dos estimadores. Os receptores com equalizaÃÃo nÃo-linear sÃo baseados no cancelamento de interferÃncia sucessiva (SIC). Neste trabalho, à proposta uma modificaÃÃo no algoritmo do SIC original, resultando em uma nova arquitetura de equalizaÃÃo. O desempenho dos receptores propostos à avaliado em diferentes condiÃÃes de nÃmero de portadoras e de grau de superposiÃÃo espectral atravÃs de simulaÃÃo computacional. Por fim, sÃo apresentados as conlusÃes e as perspectivas futuras de pesquisa. / This work presents studies on communication systems, whose signals used for transmission of information are non-orthogonal, overlapping in frequency and carrier spacing less than the rate of symbols. The research is aimed to obtain structures of transmitter, optimal and sub-optimal receivers using modeling and mathematical analysis of systems including the channel. Furthermore, propose strategies for symbol detection and performance evaluation. Seven strategies of reception to N signals m-QAM non-orthogonal through the AWGN channel. Among the strategies of detection two are optimal and the others five are suboptimal. The two optimal receivers structures presented in this paper are: the classical receiver maximum likelihood (ML) receiver and maximum likelihood based on the Gram-Schmidt decomposition. The suboptimal receivers in this work are of two types: receivers with linear and nonlinear equalization. The first type of receiver is developed based on the criteria of minimum mean square error (MMSE) and the zero forcing (ZF). It is presented the development of analytical design of each linear receiver architectures, as well as determined the error of the estimators. The receivers with nonlinear equalization are based on successive interference cancellation (SIC). In this paper, we propose a modification to the original algorithm of SIC, resulting in a new architecture of equalization. The performance of the proposed receivers is evaluated under different number of carriers and the degree of spectral overlap using computer simulation. Finally, we present the conclusions of this work and future prospects of the research.

This thesis presents a comparison of a GPU implementation of the Conjugate Residual method as a sequence of generic library kernels against implementations ofthe method with custom kernels to expose the performance gains of a keyoptimization strategy, kernel fusion, for memory-bound operations which is to makeefficient reuse of the processed data. For massive MIMO the iterative solver is to be employed at the linear detection stageto overcome the computational bottleneck of the matrix inversion required in theequalization process, which is 𝒪(𝑛3) for direct solvers. A detailed analysis of howone more of the Krylov subspace methods that is feasible for massive MIMO can beimplemented on a GPU as a unified kernel is given. Further, to show that kernel fusion can improve the execution performance not onlywhen the input data is large matrices-vectors as in scientific computing but also inthe case of massive MIMO and possibly similar cases where the input data is a largenumber of small matrices-vectors that must be processed in parallel.In more details, focusing on the small number of iterations required for the solver toachieve a close enough approximation of the exact solution in the case of massiveMIMO, and the case where the number of users matches the size of a warp, twodifferent approaches that allow to fully unroll the algorithm and gradually fuse allthe separate kernels into a single, until reaching a top-down hardcodedimplementation are proposed and tested. Targeting to overcome the algorithms computational burden which is the matrixvector product, further optimization techniques such as two ways to utilize the faston-chip memories, preloading the matrix in shared memory and preloading thevector in shared memory, are tested and proposed to achieve high efficiency andhigh parallelism.

No / Study is presented into the performance of Fast Fourier Transform (FFT) and Discrete Wavelet Transform (DWT) and MIMO-DWT with transmit beamforming. Feedback loop has been used between the equalizer at the transmitter to the receiver which provided the channel state information which was then used to construct a steering matrix for the transmission sequence such that the received signals at the transmitter can be combined constructively in order to provide a reliable and improved system for next generation wireless systems. As convolution in time domain equals multiplication in frequency domain no such counterpart exist for the symbols in space, means linear convolution and Intersymbol Interference (ISI) generation so both zero forcing (ZF) and minimum mean squared error (MMSE) equalizations have been employed. The results show superior performance improvement and in addition allow keeping the processing, power and implementation cost at the transmitter which has less constraints and the results also show that both equalization algorithms perform alike in wavelets and the ISI is spread equally between different wavelet domains.

Space-Time Block Coding is an efficient communication technique used in multiple-input multiple-output wireless systems. The complexity with which a Space-Time Block Code (STBC) can be decoded is important from an implementation point of view since it directly affects the receiver complexity and speed. In this thesis, we address the problem of designing low complexity decoding techniques for STBCs, and constructing STBCs that achieve high rate and full-diversity with these decoders. This thesis is divided into two parts; the first is concerned with the optimal decoder, viz. the maximum-likelihood (ML) decoder, and the second with non-ML decoders. An STBC is said to be multigroup ML decodable if the information symbols encoded by it can be partitioned into several groups such that each symbol group can be ML decoded independently of the others, and thereby admitting low complexity ML decoding. In this thesis, we first give a new framework for constructing low ML decoding complexity STBCs using codes over the Klein group, and show that almost all known low ML decoding complexity STBCs can be obtained by this method. Using this framework we then construct new full-diversity STBCs that have the least known ML decoding complexity for a large set of choices of number of transmit antennas and rate. We then introduce the notion of Asymptotically-Good (AG) multigroup ML decodable codes, which are families of multigroup ML decodable codes whose rate increases linearly with the number of transmit antennas. We give constructions for full-diversity AG multigroup ML decodable codes for each number of groups g > 1. For g > 2, these are the first instances of g-group ML decodable codes that are AG or have rate more than 1. For g = 2 and identical delay, the new codes match the known families of AG codes in terms of rate. In the final section of the first part we show that the upper triangular matrix R encountered during the sphere-decoding of STBCs can be rank-deficient, thus leading to higher sphere-decoding complexity, even when the rate is less than the minimum of the number of transmit antennas and the number receive antennas. We show that all known AG multigroup ML decodable codes suffer from such rank-deficiency, and we explicitly derive the sphere-decoding complexities of most known AG multigroup ML decodable codes. In the second part of this thesis we first study a low complexity non-ML decoder introduced by Guo and Xia called Partial Interference Cancellation (PIC) decoder. We give a new full-diversity criterion for PIC decoding of STBCs which is equivalent to the criterion of Guo and Xia, and is easier to check. We then show that Distributed STBCs (DSTBCs) used in wireless relay networks can be full-diversity PIC decoded, and we give a full-diversity criterion for the same. We then construct full-diversity PIC decodable STBCs and DSTBCs which give higher rate and better error performance than known multigroup ML decodable codes for similar decoding complexity, and which include other known full-diversity PIC decodable codes as special cases. Finally, inspired by a low complexity essentially-ML decoder given by Sirianunpiboon et al. for the two and three antenna Perfect codes, we introduce a new non-ML decoder called Adaptive Conditional Zero-Forcing (ACZF) decoder which includes the technique of Sirianunpiboon et al. as a special case. We give a full-diversity criterion for ACZF decoding, and show that the Perfect codes for two, three and four antennas, the Threaded Algebraic Space-Time code, and the 4 antenna rate 2 code of Srinath and Rajan satisfy this criterion. Simulation results show that the proposed decoder performs identical to ML decoding for these five codes. These STBCs along with ACZF decoding have the best error performance with least complexity among all known STBCs for four or less transmit antennas.

Abstract This thesis concentrates on the design and evaluation of spatial user multiplexing methods via linear transmit-receive processing for wireless cellular multi-user multiple-input multiple-output (MIMO) communication systems operating in the time-division duplexing (TDD) mode. The main focus is on the acquisition of effective channel state information (CSI) that facilitates decentralized processing so that the network nodes – base stations (BS) and user terminals (UT), each employing an arbitrary number of antenna elements – are able to locally participate in the network adaptation. The proposed methods rely on the uplink-downlink channel reciprocity and spatially precoded over-the-air pilot signaling. Considering (single-cell) multi-user MIMO systems, coordinated zero-forcing transmit-receive processing schemes for the uplink (UL) are proposed. The BS computes the transmission parameters in a centralized manner and employs downlink (DL) pilot signals to convey the information of the beamformers to be used by the UTs. When coexisting with the DL zero-forcing, the precoded DL demodulation pilots can be reused for UL beam allocation, and the precoded UL demodulation pilots are reused in turn for partial channel sounding (CS). As a result, only the precoded pilot symbols are needed in both UL and DL. Moreover, a concept for reducing the number of the required orthogonal UL CS pilot resources is presented. Based on their DL channel knowledge, the multi-antenna UTs form fewer pilot beams by spatial precoding than conventionally needed when transmitting antenna-specific pilots. In the context of DL zero-forcing, when taking into account the CSI estimation error at the BS, the overhead reduction turns out to improve robustness and increase the average system capacity. Considering multi-cell multi-user MIMO systems, decentralized coordinated DL beamforming strategies based on weighted sum rate (WSR) maximization are proposed. An optimization framework where the WSR maximization is carried out via weighted sum mean-squared-error minimization is utilized, and the approach is generalized by employing antenna-specific transmit power constraints. The iterative processing consists of optimization steps that are run locally by the BSs. In one novel strategy, the coordinating cells update their transmit precoders and receivers one cell at a time, which guarantees monotonic convergence of the network-wide problem. The strategy employs separate uplink CS and busy burst pilot signaling to reveal the effective channels of the UTs to the neighboring BSs. In another novel strategy, the monotonic convergence is sacrificed to devise a faster scheme where the BSs are allowed to optimize their variables in parallel based on just the CS responses and additional low-rate backhaul information exchange. The numerical results demonstrate that WSR maximization has the desirable property that spatial user scheduling is carried out implicitly. Finally, methods for UL CS overhead reduction are presented, and the effect of CSI uncertainty is addressed. / Tiivistelmä Tämä väitöskirja keskittyy lineaarisella lähetys- ja vastaanottoprosessoinnilla toteutettavien tilajakomonikäyttömenetelmien suunnitteluun ja arviointiin langattomissa moniantennisissa solukkoverkoissa, jotka hyödyntävät aikajakodupleksointia (TDD). Erityisesti tarkastellaan efektiivisen kanavatiedon hankintaa, joka mahdollistaa hajautetun prosessoinnin siten että verkkoelementit – tukiasemat ja terminaalit, jotka kukin hyödyntävät useaa antennielementtiä – voivat osallistua paikallisesti verkon adaptaatioon. Esitetyt menetelmät perustuvat ylä- ja alalinkin kanavien resiprookkisuuteen ja tilatasossa esikoodattuun opetus- eli pilottisignalointiin ilmarajapinnan yli. Yksisoluisille monikäyttäjä- ja moniantennijärjestelmille esitetään ylälinkin koordinoituja nollaanpakottavia lähetys- ja vastaanottomenetelmiä. Tukiasema laskee lähetysparametrit keskitetysti ja käyttää pilottisignaaleja kertomaan millaista lähetyskeilanmuodostusta terminaalien tulee käyttää. Alalinkin nollaanpakotuksen yhteydessä esikoodattuja demodulaatiopilotteja voidaan uudelleenkäyttää ylälinkin lähetyskeilojen allokointiin, ja esikoodattuja ylälinkin demodulaatiopilotteja uudelleenkäytetään puolestaan osittaiseen kanavan luotaukseen (sounding). Näin ollen molempiin suuntiin tarvitaan vain esikoodatut pilotit. Lisäksi työssä esitetään menetelmä ylälinkin luotauspilottiresurssitarpeen vähentämiseksi. Kanavatietoon perustuen moniantenniset terminaalit muodostavat tilatasossa esikoodattuja pilottilähetyskeiloja, joita tarvitaan vähemmän kuin perinteisiä antennikohtaisia pilotteja. Kun otetaan huomioon kanavanestimointivirhe tukiasemassa, resurssiensäästömenetelmä parantaa häiriösietoisuutta ja nostaa järjestelmän keskimääräistä kapasiteettia alalinkin nollaanpakotuksen yhteydessä. Monisoluisille monikäyttäjä- ja moniantennijärjestelmille esitetään hajautettuja koordinoituja alalinkin keilanmuodostusstrategioita, jotka perustuvat painotetun summadatanopeuden (WSR) maksimointiin. Valitussa optimointikehyksessä WSR:n maksimointi toteutetaan painotetun summaneliövirheen minimoinnin kautta, ja työssä menettelytapa yleistetään antennikohtaisten lähetystehorajoitusten tapaukseen. Iteratiivinen prosessointi koostuu optimointiaskelista, jotka tukiasemat paikallisesti suorittavat. Yhdessä esitetyssä strategiassa yhteistoiminnalliset solut päivittävät lähettimensä ja vastaanottimensa yksi solu kerrallaan, mikä takaa verkonlaajuisen ongelmanratkaisun monotonisen konvergenssin. Tämä strategia käyttää erillisiä ylälinkin luotaussignaaleja sekä varattu-signaaleja ilmaistakseen terminaalien efektiiviset kanavat naapuritukiasemille. Toisessa strategiassa monotoninen konvergenssi uhrataan ja kehitetään nopeammin adaptoituva menetelmä, jossa tukiasemat saavat optimoida muuttujansa rinnakkain, perustuen vain luotaussignaaleihin ja tukiasemien väliseen informaationvaihtoon. Numeeriset tulokset osoittavat, että WSR:n maksimointi toteuttaa aktiivisten käyttäjien valinnan tilatasossa implisiittisesti. Lopuksi esitetään menetelmiä luotauspilottiresurssitarpeen vähentämiseksi ja käsitellään kanavatiedon epävarmuuden vaikutusta.

Multiple-input, multiple-output (MIMO) techniques have been proposed to meet the needs for higher data rates and lower delays in future wireless communication systems. The downlink capacity of multiuser MIMO systems is achieved when the system transmits to several users simultaneously. Frequently, many more users request service than the transmitter can simultaneously support. Thus, the transmitter requires a scheduling algorithm for the users, which must balance the goals of increasing throughput, reducing multiuser interference, lowering delays, ensuring fairness and quality of service (QoS), etc. In this thesis, we investigate the application of genetic algorithms (GAs) to perform scheduling in multiuser MIMO systems. GAs are a fast, suboptimal, low-complexity method of solving optimization problems, such as the maximization of a scheduling metric, and can handle arbitrary functions and QoS constraints. We first examine a system that transmits using capacity-achieving dirty paper coding (DPC). Our proposed GA structure both selects users and determines their encoding order for DPC, which affects the rates they receive. Our GA can also schedule users independently on different carriers of a multi-carrier system. We demonstrate that the GA performance is close to that of an optimal exhaustive search, but at a greatly reduced complexity. We further show that the GA convergence time can be significantly reduced by tuning the values of its parameters. While DPC is capacity-achieving, it is also very complex. Thus, we also investigate GA scheduling with two linear precoding schemes, block diagonalization and successive zero-forcing. We compare the complexity and performance of the GA with "greedy" scheduling algorithms, and find the GA is more complex, but performs better at higher signal-to-noise ratios (SNRs) and smaller user pool sizes. Both algorithms are near-optimal, yet much less complex than an exhaustive search. We also propose hybrid greedy-genetic algorithms to gain benefits from both types of algorithms. Lastly, we propose an improved method of optimizing the transmit covariance matrices for successive zero-forcing. Our algorithm significantly improves upon the performance of the existing method at medium to high SNRs, and, unlike the existing method, can maximize a weighted sum rate, which is important for fairness and QoS considerations. / Communications