Soft-decision equalization techniques for frequency selective MIMO channels

Multi-input multi-output (MIMO) technology is an emerging solution for high data rate wireless communications. We develop soft-decision based equalization techniques for frequency selective MIMO channels in the quest for low-complexity equalizers with BER performance competitive to that of ML sequence detection. We first propose soft decision equalization (SDE), and demonstrate that decision feedback equalization (DFE) based on soft-decisions, expressed via the posterior probabilities associated with feedback symbols, is able to outperform hard-decision DFE, with a low computational cost that is polynomial in the number of symbols to be recovered, and linear in the signal constellation size. Building upon the probabilistic data association (PDA) multiuser detector, we present two new MIMO equalization solutions to handle the distinctive channel memory. With their low complexity, simple implementations, and impressive near-optimum performance offered by iterative soft-decision processing, the proposed SDE methods are attractive candidates to deliver efficient reception solutions to practical high-capacity MIMO systems. Motivated by the need for low-complexity receiver processing, we further present an alternative low-complexity soft-decision equalization approach for frequency selective MIMO communication systems. With the help of iterative processing, two detection and estimation schemes based on second-order statistics are harmoniously put together to yield a two-part receiver structure: local multiuser detection (MUD) using soft-decision Probabilistic Data Association (PDA) detection, and dynamic noise-interference tracking using Kalman filtering. The proposed Kalman-PDA detector performs local MUD within a sub-block of the received data instead of over the entire data set, to reduce the computational load. At the same time, all the inter-ference affecting the local sub-block, including both multiple access and inter-symbol interference, is properly modeled as the state vector of a linear system, and dynamically tracked by Kalman filtering. Two types of Kalman filters are designed, both of which are able to track an finite impulse response (FIR) MIMO channel of any memory length. The overall algorithms enjoy low complexity that is only polynomial in the number of information-bearing bits to be detected, regardless of the data block size. Furthermore, we introduce two optional performance-enhancing techniques: cross- layer automatic repeat request (ARQ) for uncoded systems and code-aided method for coded systems. We take Kalman-PDA as an example, and show via simulations that both techniques can render error performance that is better than Kalman-PDA alone and competitive to sphere decoding. At last, we consider the case that channel state information (CSI) is not perfectly known to the receiver, and present an iterative channel estimation algorithm. Simulations show that the performance of SDE with channel estimation approaches that of SDE with perfect CSI

Contributions to adaptive equalization and timing recovery for optical storage systems

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Hybrid approximate message passing

Gaussian and quadratic approximations of message passing algorithms on graphs have attracted considerable recent attention due to their computational simplicity, analytic tractability, and wide applicability in optimization and statistical inference problems. This paper presents a systematic framework for incorporating such approximate message passing (AMP) methods in general graphical models. The key concept is a partition of dependencies of a general graphical model into strong and weak edges, with the weak edges representing interactions through aggregates of small, linearizable couplings of variables. AMP approximations based on the Central Limit Theorem can be readily applied to aggregates of many weak edges and integrated with standard message passing updates on the strong edges. The resulting algorithm, which we call hybrid generalized approximate message passing (HyGAMP), can yield significantly simpler implementations of sum-product and max-sum loopy belief propagation. By varying the partition of strong and weak edges, a performance--complexity trade-off can be achieved. Group sparsity and multinomial logistic regression problems are studied as examples of the proposed methodology.The work of S. Rangan was supported in part by the National Science Foundation under Grants 1116589, 1302336, and 1547332, and in part by the industrial affiliates of NYU WIRELESS. The work of A. K. Fletcher was supported in part by the National Science Foundation under Grants 1254204 and 1738286 and in part by the Office of Naval Research under Grant N00014-15-1-2677. The work of V. K. Goyal was supported in part by the National Science Foundation under Grant 1422034. The work of E. Byrne and P. Schniter was supported in part by the National Science Foundation under Grant CCF-1527162. (1116589 - National Science Foundation; 1302336 - National Science Foundation; 1547332 - National Science Foundation; 1254204 - National Science Foundation; 1738286 - National Science Foundation; 1422034 - National Science Foundation; CCF-1527162 - National Science Foundation; NYU WIRELESS; N00014-15-1-2677 - Office of Naval Research

Self-concatenated coding for wireless communication systems

In this thesis, we have explored self-concatenated coding schemes that are designed for transmission over Additive White Gaussian Noise (AWGN) and uncorrelated Rayleigh fading channels. We designed both the symbol-based Self-ConcatenatedCodes considered using Trellis Coded Modulation (SECTCM) and bit-based Self- Concatenated Convolutional Codes (SECCC) using a Recursive Systematic Convolutional (RSC) encoder as constituent codes, respectively. The design of these codes was carried out with the aid of Extrinsic Information Transfer (EXIT) charts. The EXIT chart based design has been found an efficient tool in finding the decoding convergence threshold of the constituent codes. Additionally, in order to recover the information loss imposed by employing binary rather than non-binary schemes, a soft decision demapper was introduced in order to exchange extrinsic information withthe SECCC decoder. To analyse this information exchange 3D-EXIT chart analysis was invoked for visualizing the extrinsic information exchange between the proposed Iteratively Decoding aided SECCC and soft-decision demapper (SECCC-ID). Some of the proposed SECTCM, SECCC and SECCC-ID schemes perform within about 1 dB from the AWGN and Rayleigh fading channels’ capacity. A union bound analysis of SECCC codes was carried out to find the corresponding Bit Error Ratio (BER) floors. The union bound of SECCCs was derived for communications over both AWGN and uncorrelated Rayleigh fading channels, based on a novel interleaver concept.Application of SECCCs in both UltraWideBand (UWB) and state-of-the-art video-telephone schemes demonstrated its practical benefits.In order to further exploit the benefits of the low complexity design offered by SECCCs we explored their application in a distributed coding scheme designed for cooperative communications, where iterative detection is employed by exchanging extrinsic information between the decoders of SECCC and RSC at the destination. In the first transmission period of cooperation, the relay receives the potentially erroneous data and attempts to recover the information. The recovered information is then re-encoded at the relay using an RSC encoder. In the second transmission period this information is then retransmitted to the destination. The resultant symbols transmitted from the source and relay nodes can be viewed as the coded symbols of a three-component parallel-concatenated encoder. At the destination a Distributed Binary Self-Concatenated Coding scheme using Iterative Decoding (DSECCC-ID) was employed, where the two decoders (SECCC and RSC) exchange their extrinsic information. It was shown that the DSECCC-ID is a low-complexity scheme, yet capable of approaching the Discrete-input Continuous-output Memoryless Channels’s (DCMC) capacity.Finally, we considered coding schemes designed for two nodes communicating with each other with the aid of a relay node, where the relay receives information from the two nodes in the first transmission period. At the relay node we combine a powerful Superposition Coding (SPC) scheme with SECCC. It is assumed that decoding errors may be encountered at the relay node. The relay node then broadcasts this information in the second transmission period after re-encoding it, again, using a SECCC encoder. At the destination, the amalgamated block of Successive Interference Cancellation (SIC) scheme combined with SECCC then detects and decodes the signal either with or without the aid of a priori information. Our simulation results demonstrate that the proposed scheme is capable of reliably operating at a low BER for transmission over both AWGN and uncorrelated Rayleigh fading channels. We compare the proposed scheme’s performance to a direct transmission link between the two sources having the same throughput

Lightly synchronized Multipacket Reception in Machine-Type Communications Networks

Machine Type Communication (MTC) applications were designed to monitor and control elements of our surroundings and environment. MTC applications have a different set of requirements compared to the traditional communication devices, with Machine to Machine (M2M) data being mostly short, asynchronous, bursty and sometimes requiring end-to-end delays below 1ms. With the growth of MTC, the new generation of mobile communications has to be able to present different types of services with very different requirements, i.e. the same network has to be capable of "supplying" connection to the user that just wants to download a video or use social media, allowing at the same time MTC that has completely different requirements, without deteriorating both experiences. The challenges associated to the implementation of MTC require disruptive changes at the Physical (PHY) and Medium Access Control (MAC) layers, that lead to a better use of the spectrum available. The orthogonality and synchronization requirements of the PHY layer of current Long Term Evolution Advanced (LTE-A) radio access network (based on glsofdm and Single Carrier Frequency Domain Equalization (SC-FDE)) are obstacles for this new 5th Generation (5G) architecture. Generalized Frequency Division Multiplexing (GFDM) and other modulation techniques were proposed as candidates for the 5G PHY layer, however they also suffer from visible degradation when the transmitter and receiver are not synchronized, leading to a poor performance when collisions occur in an asynchronous MAC layer. This dissertation addresses the requirements of M2M traffic at the MAC layer applying multipacket reception (MPR) techniques to handle the bursty nature of the traffic and synchronization tones and optimized back-off approaches to reduce the delay. It proposes a new MAC protocol and analyses its performance analytically considering an SC-FDE modulation. The models are validated using a system level cross-layer simulator developed in MATLAB, which implements the MAC protocol and applies PHY layer performance models. The results show that the MAC’s latency depends mainly on the number of users and the load of each user, and can be controlled using these two parameters