Information Theory Applications in Signal Processing

Ministerio de Economía, Industria y Competitividad (MINECO) TEC2017-82807-PMinisterio de Economía, Industria y Competitividad (MINECO) TEC2014-53103-

Joint waveform and precoding design for coexistence of MIMO radar and MU-MISO communication

peer reviewedThe joint design problem for the coexistence of multiple-input multiple-output (MIMO) radar and multi-user multiple-input-single-output (MU-MISO) communication is investigated. Different from the conventional design schemes, which require defining the primary function, we consider designing the transmit waveform, precoding matrix and receive filter to maximize the radar SINR and the minimal SINR of communication users, simultaneously. By doing so, the promising overall performance for both sensing and communication is achieved without requiring parameter tuning for the threshold of communication or radar. However, the resulting optimization problem which contains the maximin objective function and the unit sphere constraint, is highly nonconvex and hence difficult to attain the optimal solution directly. Towards this end, the epigraph-form reformulation is first adopted, and then an alternating maximisation (AM) method is devised, in which the Dinkelbach’s algorithm is used to tackle the nonconvex fractional-programing subproblem. Simulation results indicate that the proposed method can achieve improved performance compared with the benchmarks

Advanced Coding And Modulation For Ultra-wideband And Impulsive Noises

The ever-growing demand for higher quality and faster multimedia content delivery over short distances in home environments drives the quest for higher data rates in wireless personal area networks (WPANs). One of the candidate IEEE 802.15.3a WPAN proposals support data rates up to 480 Mbps by using punctured convolutional codes with quadrature phase shift keying (QPSK) modulation for a multi-band orthogonal frequency-division multiplexing (MB-OFDM) system over ultra wideband (UWB) channels. In the first part of this dissertation, we combine more powerful near-Shannon-limit turbo codes with bandwidth efficient trellis coded modulation, i.e., turbo trellis coded modulation (TTCM), to further improve the data rates up to 1.2 Gbps. A modified iterative decoder for this TTCM coded MB-OFDM system is proposed and its bit error rate performance under various impulsive noises over both Gaussian and UWB channel is extensively investigated, especially in mismatched scenarios. A robust decoder which is immune to noise mismatch is provided based on comparison of impulsive noises in time domain and frequency domain. The accurate estimation of the dynamic noise model could be very difficult or impossible at the receiver, thus a significant performance degradation may occur due to noise mismatch. In the second part of this dissertation, we prove that the minimax decoder in \cite, which instead of minimizing the average bit error probability aims at minimizing the worst bit error probability, is optimal and robust to certain noise model with unknown prior probabilities in two and higher dimensions. Besides turbo codes, another kind of error correcting codes which approach the Shannon capacity is low-density parity-check (LDPC) codes. In the last part of this dissertation, we extend the density evolution method for sum-product decoding using mismatched noises. We will prove that as long as the true noise type and the estimated noise type used in the decoder are both binary-input memoryless output symmetric channels, the output from mismatched log-likelihood ratio (LLR) computation is also symmetric. We will show the Shannon capacity can be evaluated for mismatched LLR computation and it can be reduced if the mismatched LLR computation is not an one-to-one mapping function. We will derive the Shannon capacity, threshold and stable condition of LDPC codes for mismatched BIAWGN and BIL noise types. The results show that the noise variance estimation errors will not affect the Shannon capacity and stable condition, but the errors do reduce the threshold. The mismatch in noise type will only reduce Shannon capacity when LLR computation is based on BIL

MIMO Systems

In recent years, it was realized that the MIMO communication systems seems to be inevitable in accelerated evolution of high data rates applications due to their potential to dramatically increase the spectral efficiency and simultaneously sending individual information to the corresponding users in wireless systems. This book, intends to provide highlights of the current research topics in the field of MIMO system, to offer a snapshot of the recent advances and major issues faced today by the researchers in the MIMO related areas. The book is written by specialists working in universities and research centers all over the world to cover the fundamental principles and main advanced topics on high data rates wireless communications systems over MIMO channels. Moreover, the book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Beamforming optimization for two-way relay channel

In this thesis, we focus on the optimization of the two-way relay channel (TWRC), which can double the data rate of communications comparing to the traditional one-way relay channel (OWRC). Because of the broadcasting nature of wireless transmissions, secure transmission is an appealing research topic. We take secrecy rate consideration into the optimization of the TWRC. Overall we provide near-optimal solutions for the secrecy rate maximization problems of the TWRC with imperfect channel state information (ICSI). A much lower complexity optimal SOCP solution is provided for SNR balancing of the TWRC without secrecy consideration. We first look at a flat fading TWRC network model with a multiple-input multiple-output (MIMO) relay where perfect channel state information (CSI) is assumed available. We then formulate an optimization problem, with the objective to minimize the relay’s power usage under the constraints that the signal-to-noise ratio (SNR) of the two transceivers should exceed a preset threshold. A low-complexity optimal beamforming solution is provided to this optimization problem by reformulating it in the form of second-order cone programming (SOCP). Later in the thesis, we consider the presence of an eavesdropper and address the beamforming optimization for minimizing the relay’s power with the constraints of the secrecy rates of the two transceivers. A semi-definite programming (SDP) based searching algorithm is proposed to find a near-optimal solution. For each search of the proposed approach, the previous non-convex optimization problem is transferred into an SDP problem, which can guarantee the optimality of the beamforming matrix. Afterwards, more realistic imperfect CSI (ICSI) situations are considered for the TWRC network models. As ICSI completely changes the structure and the property of the optimization problems, we reformulate the optimization problems into two scenarios. For the first case, we consider that the relay is an untrusted eavesdropper and in this case an SDP solution is provided to maximize the joint-decoding sum-secrecy rate. For the second case, we investigate the robust beamforming problems where the relay is trusted but there is an external eavesdropper, another SDP solution is provided to maximize the sum-secrecy rate