FPGA based Soft-core SIMD Processing: A MIMO-OFDM Fixed-Complexity Sphere Decoder Case Study

To enable reliable data transfer in next generation Multiple-Input Multiple-Output (MIMO) communication systems, terminals must be able to react to fluctuating channel conditions by having flexible modulation schemes and antenna configurations. This creates a challenging real-time implementation problem: to provide the high performance required of cutting edge MIMO standards, such as 802.11n, with the flexibility for this behavioural variability. FPGA softcore processors offer a solution to this problem, and in this paper we show how heterogeneous SISD/SIMD/MIMD architectures can enable programmable multicore architectures on FPGA with similar performance and cost as traditional dedicated circuit-based architectures. When applied to a 4×4 16-QAM Fixed-Complexity Sphere Decoder (FSD) detector we present the first soft-processor based solution for real-time 802.11n MIMO.

Inverse Gaussian Modeling of Turbulence-Induced Fading in Free-Space Optical Systems

We propose the inverse Gaussian distribution, as a less complex alternative to the classical log-normal model, to describe turbulence-induced fading in free-space optical (FSO) systems operating in weak turbulence conditions and/or in the presence of aperture averaging effects. By conducting goodness of fit tests, we define the range of values of the scintillation index for various multiple-input multiple-output (MIMO) FSO configurations, where the two distributions approximate each other with a certain significance level. Furthermore, the bit error rate performance of two typical MIMO FSO systems is investigated over the new turbulence model; an intensity-modulation/direct detection MIMO FSO system with Q-ary pulse position modulation that employs repetition coding at the transmitter and equal gain combining at the receiver, and a heterodyne MIMO FSO system with differential phase-shift keying and maximal ratio combining at the receiver. Finally, numerical results are presented that validate the theoretical analysis and provide useful insights into the implications of the model parameters on the overall system performance. © 2011 IEEE.

Massive MIMO with Optimal Power and Training Duration Allocation

We consider the uplink of massive multicell multiple-input multiple-output systems, where the base stations (BSs), equipped with massive arrays, serve simultaneously several terminals in the same frequency band. We assume that the BS estimates the channel from uplink training, and then uses the maximum ratio combining technique to detect the signals transmitted from all terminals in its own cell. We propose an optimal resource allocation scheme which jointly selects the training duration, training signal power, and data signal power in order to maximize the sum spectral efficiency, for a given total energy budget spent in a coherence interval. Numerical results verify the benefits of the optimal resource allocation scheme. Furthermore, we show that more training signal power should be used at low signal-to-noise ratio (SNRs), and vice versa at high SNRs. Interestingly, for the entire SNR regime, the optimal training duration is equal to the number of terminals.

Improving Bandwidth Efficiency in E-band Communication Systems

The allocation of a large amount of bandwidth by regulating bodies in the 70/80 GHz band, i.e., the E-band, has opened up new potentials and challenges for providing affordable and reliable Gigabit per second wireless point-to-point links. This article first reviews the available bandwidth and licensing regulations in the E-band. Subsequently, different propagation models, e.g., the ITU-R and Cane models, are compared against measurement results and it is concluded that to meet specific availability requirements, E-band wireless systems may need to be designed with larger fade margins compared to microwave systems. A similar comparison is carried out between measurements and models for oscillator phase noise. It is confirmed that phase noise characteristics, that are neglected by the models used for narrowband systems, need to be taken into account for the wideband systems deployed in the E-band. Next, a new multi-input multi-output (MIMO) transceiver design, termed continuous aperture phased (CAP)-MIMO, is presented. Simulations show that CAP-MIMO enables E-band systems to achieve fiber-optic like throughputs. Finally, it is argued that full-duplex relaying can be used to greatly enhance the coverage of E-band systems without sacrificing throughput, thus, facilitating their application in establishing the backhaul of heterogeneous networks.

Secure Transmission in MIMO Wiretap Channels Using General-Order Transmit Antenna Selection with Outdated CSI

In this paper, we propose general-order transmit antenna selection to enhance the secrecy performance of multiple-input–multiple-output multieavesdropper channels with outdated channel state information (CSI) at the transmitter. To evaluate the effect of the outdated CSI on the secure transmission of the system, we investigate the secrecy performance for two practical scenarios, i.e., Scenarios I and II, where the eavesdropper's CSI is not available at the transmitter and is available at the transmitter, respectively. For Scenario I, we derive exact and asymptotic closed-form expressions for the secrecy outage probability in Nakagami- m fading channels. In addition, we also derive the probability of nonzero secrecy capacity and the \varepsilon -outage secrecy capacity, respectively. Simple asymptotic expressions for the secrecy outage probability reveal that the secrecy diversity order is reduced when the CSI is outdated at the transmitter, and it is independent of the number of antennas at each eavesdropper N_text\rm{E} , the fading parameter of the eavesdropper's channel m_text\rm{E} , and the number of eavesdroppers M . For Scenario II, we make a comprehensive analysis of the average secrecy capacity obtained by the system. Specifically, new closed-form expressions for the exact and asymptotic average secrecy capacity are derived, which are valid for general systems with an arbitrary number of antennas, number of eavesdroppers, and fading severity parameters. Resorting to these results, we also determine a high signal-to-noise ratio power offset to explicitly quantify the impact of the main c- annel and the eavesdropper's channel on the average secrecy capacity.

Statistical Eigenmode Transmission for the MU-MIMO Downlink in Rician Fading

In this paper, we study the achievable ergodic sum-rate of multiuser multiple-input multiple-output downlink systems in Rician fading channels. We first derive a lower bound on the average signal-to-leakage-and-noise ratio by using the Mullen’s inequality, and then use it to analyze the effect of channel mean information on the achievable ergodic sum-rate. A novel statistical-eigenmode space-division multiple-access (SESDMA) downlink transmission scheme is then proposed. For this scheme, we derive an exact analytical closed-form expression for the achievable ergodic rate and present tractable tight upper and lower bounds. Based on our analysis, we gain valuable insights into the system parameters, such as the number of transmit antennas, the signal-to-noise ratio (SNR) and Rician K-factor on the system sum-rate. Results show that the sum-rate converges to a saturation value in the high SNR regime and tends to a lower limit for the low Rician K-factor case. In addition, we compare the achievable ergodic sum-rate between SE-SDMA and zeroforcing beamforming with perfect channel state information at the base station. Our results reveal that the rate gap tends to zero in the high Rician K-factor regime. Finally, numerical results are presented to validate our analysis.

Channel and frequency offset estimation schemes for multicarrier systems

O presente trabalho aborda o problema da estimação de canal e da estimação de desvio de frequência em sistemas OFDM com múltiplas configurações de antenas no transmissor e no receptor. Nesta tese é apresentado o estudo teórico sobre o impacto da densidade de pilotos no desempenho da estimação de canal em sistemas OFDM e são propostos diversos algoritmos para estimação de canal e estimação de desvio de frequência em sistemas OFDM com antenas únicas no transmissor e receptor, com diversidade de transmissão e MIMO. O estudo teórico culmina com a formulação analítica do erro quadrático médio de um estimador de canal genérico num sistema OFDM que utilize pilotos dedicados, distribuidos no quadro transmitido em padrões bi-dimensionais. A formulação genérica é concretizada para o estimador bi-dimensional LS-DFT, permitindo aferir da exactidão da formulação analítica quando comparada com os valores obtidos por simulação do sistema abordado. Os algoritmos de estimação investigados tiram partido da presença de pilotos dedicados presentes nos quadros transmitidos para estimar com precisão os parâmetros pretendidos. Pela sua baixa complexidade, estes algoritmos revelam-se especialmente adequados para implementação em terminais móveis com capacidade computacional e consumo limitados. O desempenho dos algoritmos propostos foi avaliado por meio de simulação do sistema utilizado, recorrendo a modelos aceites de caracterização do canal móvel multipercurso. A comparação do seu desempenho com algoritmos de referência permitir aferir da sua validade. ABSTRACT: The present work focus on the problem of channel estimation and frequency offset estimation in OFDM systems, with different antenna configurations at both the transmitter and the receiver. This thesis presents the theoretical study of the impact of the pilot density in the performance of the channel estimation in OFDM systems and proposes several channel and frequency offset algorithms for OFDM systems with single antenna at both transmitter and receiver, with transmitter diversity and MIMO. The theoretical study results in the analytical formulation of the mean square error of a generic channel estimator for an OFDM system using dedicated pilots, distributed in the transmitted frame in two-dimensional patterns. The generic formulation is implemented for the two-dimensional LS-DFT estimator to verify the accuracy of the analytical formulation when compared with the values obtained by simulation of the discussed system. The investigated estimation algorithms take advantage of the presence of dedicated pilots present in the transmitted frames to accurately estimate the required parameters. Due to its low complexity, these algorithms are especially suited for implementation in mobile terminals with limited processing power and consumption. The performance of the proposed algorithms was evaluated by simulation of the used system, using accepted multipath mobile channel models. The comparison of its performance with the one of reference algorithms measures its validity.

Interference cancellation for distributed wireless systems

O tema principal desta tese é o problema de cancelamento de interferência para sistemas multi-utilizador, com antenas distribuídas. Como tal, ao iniciar, uma visão geral das principais propriedades de um sistema de antenas distribuídas é apresentada. Esta descrição inclui o estudo analítico do impacto da ligação, dos utilizadores do sistema, a mais antenas distribuídas. Durante essa análise é demonstrado que a propriedade mais importante do sistema para obtenção do ganho máximo, através da ligação de mais antenas de transmissão, é a simetria espacial e que os utilizadores nas fronteiras das células são os mais bene ciados. Tais resultados são comprovados através de simulação. O problema de cancelamento de interferência multi-utilizador é considerado tanto para o caso unidimensional (i.e. sem codi cação) como para o multidimensional (i.e. com codi cação). Para o caso unidimensional um algoritmo de pré-codi cação não-linear é proposto e avaliado, tendo como objectivo a minimização da taxa de erro de bit. Tanto o caso de portadora única como o de multipla-portadora são abordados, bem como o cenário de antenas colocadas e distribuidas. É demonstrado que o esquema proposto pode ser visto como uma extensão do bem conhecido esquema de zeros forçados, cuja desempenho é provado ser um limite inferior para o esquema generalizado. O algoritmo é avaliado, para diferentes cenários, através de simulação, a qual indica desempenho perto do óptimo, com baixa complexidade. Para o caso multi-dimensional um esquema para efectuar "dirty paper coding" binário, tendo como base códigos de dupla camada é proposto. No desenvolvimento deste esquema, a compressão com perdas de informação, é considerada como um subproblema. Resultados de simulação indicam transmissão dedigna proxima do limite de Shannon.

Compensation of undesired effects in MIMO wireless transceivers

This paper presents compensation of all undesired effects (Power Amplifier (PA) nonlinearity, transmitter and receiver antenna crosstalk, before-PA nonlinear crosstalk, Multiple Input Multiple Output (MIMO) channel fading and crosstalk) in MIMO Orthogonal Frequency Division Multiplex (OFDM) wireless systems. It has been demonstrated that reduced-complexity Crossover Digital Predistortion (CO-DPD) algorithm on transmitter side and Matrix Inversion algorithm on receiver side can suppress almost all undesired effects introduced by transmitter, channel and receiver in 4×4 MIMO OFDM System that can be used in modern wireless system applications. A significant complexity reduction is achieved due to the fact that Digital Signal Processing (DSP) during CO-DPD process on transmitter side is done with real instead of complex numbers.

A novel blind channel estimation method for MIMO system

Channel estimation method is a key issue in MIMO system. In recent years, a lot of papers on subspace(SS)-based blind channel estimation have been published, and in this paper, combining SS method with a space-time coding scheme, we proposed a novel blind channel estimation method in MIMO system. Simulation result demonstrates the effectiveness of this method.

A semi-blind reception scheme based on ICA for multiuser MIMO-STBC system

When the orthogonal space-time block code (STBC), or the Alamouti code, is applied on a multiple-input multiple-output (MIMO) communications system, the optimum reception can be achieved by a simple signal decoupling at the receiver. The performance, however, deteriorates significantly in presence of co-channel interference (CCI) from other users. In this paper, such CCI problem is overcome by applying the independent component analysis (ICA), a blind source separation algorithm. This is based on the fact that, if the transmission data from every transmit antenna are mutually independent, they can be effectively separated at the receiver with the principle of the blind source separation. Then equivalently, the CCI is suppressed. Although they are not required by the ICA algorithm itself, a small number of training data are necessary to eliminate the phase and order ambiguities at the ICA outputs, leading to a semi-blind approach. Numerical simulation is also shown to verify the proposed ICA approach in the multiuser MIMO system.

Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

Variable selection algorithm for the construction of MIMO operating point dependent neurofuzzy networks

An input variable selection procedure is introduced for the identification and construction of multi-input multi-output (MIMO) neurofuzzy operating point dependent models. The algorithm is an extension of a forward modified Gram-Schmidt orthogonal least squares procedure for a linear model structure which is modified to accommodate nonlinear system modeling by incorporating piecewise locally linear model fitting. The proposed input nodes selection procedure effectively tackles the problem of the curse of dimensionality associated with lattice-based modeling algorithms such as radial basis function neurofuzzy networks, enabling the resulting neurofuzzy operating point dependent model to be widely applied in control and estimation. Some numerical examples are given to demonstrate the effectiveness of the proposed construction algorithm.