In this work wireless communication systems with multiple co-channel signals present at the receiver are considered. One of the major challenges in the development of such systems is the computational complexity required for the detection of the transmitted signals. This thesis addresses this problem and develops reduced complexity algorithms for the detection of multiple co-channel signals in receivers with multiple antennas. The signals are transmitted from either a single user employing multiple transmit antennas, from multiple users or in the most general case by a mixture of the two. The receiver is assumed to be overloaded in that the number of transmitted signals exceeds the number of receive antennas. Joint Maximum Likelihood (JML) is the optimum detection algorithm which has exponential complexity in the number of signals. As a result, detection of the signals of interest at the receiver is challenging and infeasible in most practical systems. The thesis presents a framework for the detection of multiple co-channel signals in overloaded receivers. It proposes receiver structures and two list-based signal detection algorithms that allow for complexity reduction compared to the optimum detector while being able to maintain near optimum performance. Complexity savings are achieved by first employing a linear preprocessor at the receiver to reduce the effect of Co-Channel Interference (CCI) and second, by using a detection algorithm that searches only over a subspace of the transmitted symbols. Both algorithms use iterative processing to extract ordered lists of the most likely transmit symbols. Soft information can be obtained from the detector output list and can then be used by error control decoders. The first algorithm named Parallel Detection with Interference Estimation (PD-IE) considers the Additive White Gaussian Noise (AWGN) channel. It relies on a spatially reduced search over subsets of the transmitted symbols in combination with CCI estimation. Computational complexity under overload is lower than that of JML. Performance results show that PD-IE achieves near optimum performance in receivers with Uniform Circular Array (UCA) and Uniform Linear Array (ULA) antenna geometries. The second algorithm is referred to as List Group Search (LGS) detection. It is applied to overloaded receivers that operate in frequency-flat multipath fading channels. The List Group Search (LGS) detection algorithm forms multiple groups of the transmitted symbols over which an exhaustive search is performed. Simulation results show that LGS detection provides good complexity-performance tradeoffs under overload. A union bound for group-wise and list-based group-wise symbol detectors is also derived. It provides an approximation to the error performance of such detectors without the need for simulation. Moreover, the bound can be used to determine some detection parameters and tradeoffs. Results show that the bound is tight in the high Signal to Interference and Noise Ratio (SINR) region.

Abstract Iterative receiver techniques, multiple-input – multiple-output (MIMO) processing, and orthogonal frequency division multiplexing (OFDM) are amongst the key physical layer technologies when aiming at higher spectral efficiency for a wireless communication system. Special focus is put on iterative detection, decoding, and channel estimation for a MIMO-OFDM system. After designing separately efficient algorithms for the detection, channel decoding, and channel estimation, the objective is to optimize them to work together through optimizing the activation schedules for soft-in soft-out (SfISfO) components. A list parallel interference cancellation (PIC) detector is derived to approximate an a posteriori probability (APP) algorithm with reduced complexity and minimal loss of performance. It is shown that the list PIC detector with good initialization outperforms the K-best list sphere detector (LSD) in the case of small list sizes, whereas the complexities of the algorithms are of the same order. The convergence of the iterative detection and decoding is improved by using a priori information to also recalculate the candidate list, aside from the log-likelihood ratios (LLRs) of the coded bits. Unlike in pilot based channel estimation, the least-squares (LS) channel estimator based on symbol decisions requires a matrix inversion in MIMO-OFDM. The frequency domain (FD) space-alternating generalized expectation-maximization (SAGE) channel estimator calculates the LS estimate iteratively, avoiding the matrix inversion with constant envelope modulation. The performance and computational complexity of the FD-SAGE channel estimator are compared to those of pilot based LS channel estimation with minimum mean square error (MMSE) post-processing exploiting the time correlation of the channel. A time domain (TD) SAGE channel estimator is derived to avoid the matrix inversion in channel estimation based on symbol decisions for MIMO-OFDM systems also with non-constant envelope modulation. An obvious problem, with more than two blocks in an iterative receiver, is to find the optimal activation schedule of the different blocks. It is proposed to use extrinsic information transfer (EXIT) charts to characterize the behavior of the receiver blocks and to find out the optimal activation schedule for them. A semi-analytical expression of the EXIT function is derived for the LS channel estimator. An algorithm is proposed to generate the EXIT function of the APP algorithm as a function of the channel estimate’s mutual information (MI). Surface fitting is used to get closed form expressions for the EXIT functions of the APP algorithm and the channel decoder. Trellis search algorithms are shown to find the convergence with the lowest possible complexity using the EXIT functions. With the proposed concept, the activation scheduling can be adapted to prevailing channel circumstances and unnecessary iterations will be avoided.

Abstract The multiple-input multiple-output (MIMO) technique combined with an orthogonal frequency division multiplexing (MIMO--OFDM) has been introduced as a promising approach for the ever increasing capacity and quality of service (QoS) requirements for wireless communication systems. An efficient radio spectrum utilization expects a flexible transceiver solution, which has been the reason for the development of the software defined radio (SDR) technologies which in their turn are expected to enable the creation of cognitive radios. As a result, any radio solution could be invoked on demand on any platform. In this thesis work, we have studied detector algorithms and programmable processor architectures in order to find practical solutions for the future wireless systems. A programmable receiver can reduce the energy dissipation of the receiver by changing the detection algorithm based on the current channel realizations. To provide a realistic aspect to the implementations in different channel realizations, we present a wide state-of-the-art detector comparison. In addition, we present an extensive number arithmetic and word length study in order to evaluate realistic hardware complexity and energy dissipations of the implementations. The study includes a comprehensive design chain from the algorithm development to the actual processor design and finally programming software for the platforms. We evaluate single and multi-core processor implementations by comparing the achieved results to the Long Term Evolution (LTE) performance requirements. We implement detectors on digital signal processors (DSPs), graphics processing unit (GPU) and transport triggered architecture (TTA). The implementation results are compared in throughput, silicon area and energy efficiency. Finally, we discuss the advantages and disadvantages of the architectures and the implementation effort. / Tiivistelmä Usean antennin tekniikka yhdistettynä ortogonaaliseen taajuusvaihtelumodulointiin lähetin-vastaanotimessa on esitetty eräänä lupaavana ratkaisuna jatkuvasti kasvaviin kapasiteetti- ja palvelunlaatuvaatimuksiin langattomissa tietoliikennejärjestelmissä. Tehokas radiospektrin käyttö edellyttää joustavaa lähetin-vastaanotinratkaisua, mikä on ollut syynä ohjelmistoradioteknologioiden kehitykselle. Ohjelmistoradioiden kehityksen on puolestaan odotettu mahdollistavan kognitiiviradioiden syntymisen. Tuloksena, mikä tahansa radiosovellus voitaisiin herättää tarpeen mukaan millä tahansa ohjelmoitavalla sovellusalustalla. Tässä väitöskirjatyössä tutkitaan ilmaisinalgoritmeja sekä ohjelmoitavia prosessoriarkkitehtuureja tarkoituksena löytää käytännöllisiä ratkaisuja tulevaisuuden langattomiin järjestelmiin. Ohjelmoitavalla vastaanottimella voidaan vähentää vastaanottimen energiankulutusta vaihtamalla ilmaisinalgoritmeja vallitsevan kanavatilan mukaan. Työssä esitellään laaja, viimeisintä tutkimusta edustava ilmaisinalgoritmivertailu, joka antaa realistisen näkökannan toteutuksiin erilaisissa kanavatiloissa. Lisäksi työssä esitellään numeroaritmetiikka- ja sananpituustutkimus, jonka tarkoituksena on arvioida toteutusten realistista kovokompleksisuutta sekä energiankulutusta. Tutkimus sisältää kattavan suunnitteluketjun algoritmikehityksestä todelliseen prosessorisuunnitteluun ja lopulta algoritmin ohjelmointiin tietylle sovellusalustalle. Väitöskirjatyössä arvioidaan yksi- ja moniytimisiä prosessoritoteutuksia vertaamalla saavutettuja tuloksia Long Term Evolution -standardin suorituskykyvaatimuksiin. Ilmaisimia toteutetaan digitaalisilla signaaliprosessoreilla, grafiikkaprosessorilla sekä siirtoliipaisuarkkitehtuurilla. Toteutustuloksia vertaillaan laskentatehona, pinta-alana sekä energiatehokkuutena. Lopuksi käsitellään arkkitehtuurien hyviä ja huonoja puolia sekä suunnittelun työläyttä.

[pt] Na primeira parte desta tese, são desenvolvidos dois esquemas de detecção por listas para sistemas MIMO multiusuário. As técnicas propostas usam uma única transformação de redução de reticulado (LR) para modificar a matriz de canal entre os usuários e a estação base (BS). Após a transformação LR, um candidato confiável do sinal transmitido é obtido usando um detector de cancelamento sucessivo de interferências (SIC). No detector em múltiplos ramos com redução de reticulado e cancelamento sucessivo de interferências (MB-LR-SIC) proposto, um número fixo de diferentes ordenamentos para o detector SIC gera uma lista de possíveis candidatos para a informação transmitida. O melhor candidato é escolhido usando o critério maximum likelihood (ML). No detector por listas de tamanho variável (VLD) proposto, um algoritmo que decide se o candidato atual tem uma boa qualidade ou se é necessário continuar procurando por um candidato melhor nos ordenamentos restantes é utilizado. Os resultados numéricos mostram que os esquemas propostos têm um desempenho quase ótimo com uma complexidade computacional bem abaixo do detector ML. Um esquema de detecção e decodificação iterativa (IDD) baseado no algoritmo VLD é também desenvolvido, produzindo um desempenho próximo a um sistema mono usuário (SU) livre de interferências. Na segunda parte desta tese, uma técnica de detecção desacoplada de sinais (DSD) para sistemas MIMO massivo é proposta. Esta técnica permite que o sinal composto recebido na BS seja separado em sinais independentes, correspondentes a diferentes classes de usuários, viabilizando assim o uso dos procedimentos de detecção propostos na primeira parte desta tese em sistemas MIMO massivos. Um modelo de sinais para sistemas MIMO massivo com antenas centralizadas e/ou antenas distribuídas operando em redes heterogêneas de quinta geração é proposto. Uma análise baseada na soma das taxas e um estudo de custo computacional para DSD são apresentados. Os resultados numéricos ilustram o excelente compromisso desempenho versus complexidade obtido com a técnica DSD quando comparada com o esquema de detecção conjunta tradicional. / [en] In the first part of this thesis, we introduce two list detection schemes for the uplink scenario of multiuser multiple-input multiple-output (MUMIMO) systems. The proposed techniques employ a single lattice reduction (LR) transformation to modify the channel matrix between the users and the base station (BS). After the LR transformation, a reliable candidate for the transmitted signal vector, provided by successive interference cancellation (SIC) detection is obtained. In the proposed multi-branch lattice reduction SIC (MB-LR-SIC) detector, a fixed number of different orderings, generates a list of SIC detection candidates. The best candidate is chosen according to the maximum likelihood (ML) selection criterion. For the proposed variable list detection (VLD) scheme, an algorithm to decide if the current candidate has good quality or if it is necessary to further explore different orderings to improve the detection performance is employed. Simulation results indicate that the proposed schemes have a near-optimal performance while keeping its computational complexity well below that of the ML detector. An iterative detection and decoding (IDD) scheme based on the VLD algorithm is also developed, producing an excellent performance that approaches the single user (SU) scenario. In the second part of this thesis, a decoupled signal detection (DSD) technique which allows the separation of uplink signals, for each user class, at the base station (BS) for massive MIMO systems is proposed. The proposed DSD allows to implement the detection procedures proposed in the first part of this thesis in massive MIMO scenarios. A mathematical signal model for massive MIMO systems with centralized and distributed antennas in the future fifth generation (5G) heterogeneous cellular networks is also developed. A sum-rate analysis and a study of computational cost for DSD are also presented. Simulation results show excellent performance of the proposed DSD algorithm when combined with linear and SIC-based detectors.