Low Dimensional MIMO Systems with Finite Sized Constellation Inputs

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Analysis and Design of Non-Orthogonal Multiple Access (NOMA) Techniques for Next Generation Wireless Communication Systems

The current surge in wireless connectivity, anticipated to amplify significantly in future wireless technologies, brings a new wave of users. Given the impracticality of an endlessly expanding bandwidth, there’s a pressing need for communication techniques that efficiently serve this burgeoning user base with limited resources. Multiple Access (MA) techniques, notably Orthogonal Multiple Access (OMA), have long addressed bandwidth constraints. However, with escalating user numbers, OMA’s orthogonality becomes limiting for emerging wireless technologies. Non-Orthogonal Multiple Access (NOMA), employing superposition coding, serves more users within the same bandwidth as OMA by allocating different power levels to users whose signals can then be detected using the gap between them, thus offering superior spectral efficiency and massive connectivity. This thesis examines the integration of NOMA techniques with cooperative relaying, EXtrinsic Information Transfer (EXIT) chart analysis, and deep learning for enhancing 6G and beyond communication systems. The adopted methodology aims to optimize the systems’ performance, spanning from bit-error rate (BER) versus signal to noise ratio (SNR) to overall system efficiency and data rates. The primary focus of this thesis is the investigation of the integration of NOMA with cooperative relaying, EXIT chart analysis, and deep learning techniques. In the cooperative relaying context, NOMA notably improved diversity gains, thereby proving the superiority of combining NOMA with cooperative relaying over just NOMA. With EXIT chart analysis, NOMA achieved low BER at mid-range SNR as well as achieved optimal user fairness in the power allocation stage. Additionally, employing a trained neural network enhanced signal detection for NOMA in the deep learning scenario, thereby producing a simpler signal detection for NOMA which addresses NOMAs’ complex receiver problem

Deep learning SIC approach for uplink MIMO-NOMA system

Abstract. Deep learning-based successive interference cancellation (DL-SIC) for uplink multiple-input multiple-output -non-orthogonal multiple access (MIMO-NOMA) system tries to optimize the users’ bit error rate (BER) and total mean square error (MSE) performance with higher order modulation schemes. The recent work of DL-SIC receiver design for users with a QPSK modulation scheme is investigated in this thesis to validate its performance as a potential alternative approach to traditional SIC receivers for NOMA users. Then, a DL-SIC receiver design for higher order modulation with less dependence on modulation order in the output layer is proposed, which enables us to decode the users with different modulation schemes. In our proposed design, we employ two deep neural networks (DNNs) for each SIC step. The system model is considered an M-antenna base station (BS) that serves two uplink users with a single antenna in the Rayleigh fading channel. The equivalent conventional minimum mean square error-based SIC (MMSE-SIC) and zero-forcing-based SIC (ZF-SIC) receivers are implemented as a baseline comparison. The simulation results showed that the BER performance of the proposed DL-SIC receiver for both users with QPSK modulation results in a 10 dB gain between BER of 10^(-2) and 10^(-3) compared to the ZF-SIC receiver. Furthermore, the performance difference between the proposed scheme and ZF-SIC is significantly high when both users transmit with 16QAM. Overall, the proposed DL-SIC receiver performs better in all signal-to-noise ratio (SNR) regions than the equivalent ZF-SIC receivers and also aids in mitigating the SIC error propagation problem. In addition, it improves the processing latency due to the benefits of the parallelized computing architecture and decreases the complexity of traditional SIC receivers

Next-generation optical access networks based on Orthogonal Frequency Division Multiplexing

Orthogonal Frequency Division Multiplexing (OFDM) is a robust modulation and multiplexing format which is at the base of many present communication standards. The interest of the OFDM application in optical fiber deployments is quite recent. As the next generation of Passive Optical Networks (NG-PONs) is envisioned, targeting greater capacity and user counts, the limitations of TDMA (Time Division Multiplexing Access) approaches to meet the expected increase in requirements becomes evident and therefore new technologies are being explored. Optical OFDMA is an emerging technology which can be a promising candidate. The main goal of this Master Thesis is to study the problem of users multiplexing in access networks, using OFDM as a technology to transmit the user information data. This work has focused in the uplink study of the network, because it is the most challenging part of the network to design. The studies have been conducted both in a theoretical way and also by simulating the targeted environments by means of a fiber optics transmission simulation tool. Virtual Photonics Integrated (VPI) is the software selected for the simulations. This tool is specially designed to simulate optical transmission system environments. The analysis of the Optical Beat Interference, which is a critical impairment in optical carrier multiplexing schemes, is the most important part of the user multiplexing study

Efficient Transmission Techniques in Cooperative Networks: Forwarding Strategies and Distributed Coding Schemes

This dissertation focuses on transmission and estimation schemes in wireless relay network, which involves a set of source nodes, a set of destination nodes, and a set of nodes helps communication between source nodes and destination nodes, called relay nodes. It is noted that the overall performance of the wireless relay systems would be impacted by the relay methods adopted by relay nodes. In this dissertation, efficient forwarding strategies and channel coding involved relaying schemes in various relay network topology are studied.First we study a simple structure of relay systems, with one source, one destination and one relay node. By exploiting “analog codes” -- a special class of error correction codes that can directly encode and protect real-valued data, a soft forwarding strategy –“analog-encode-forward (AEF)”scheme is proposed. The relay node first soft-decodes the packet from the source, then re-encodes this soft decoder output (Log Likelihood Ratio) using an appropriate analog code, and forwards it to the destination. At the receiver, both a maximum-likelihood (ML) decoder and a maximum a posterior (MAP) decoder are specially designed for the AEF scheme.The work is then extended to parallel relay networks, which is consisted of one source, one destination and multiple relay nodes. The first question confronted with us is which kind of soft information to be relayed at the relay nodes. We analyze a set of prevailing soft information for relaying considered by researchers in this field. A truncated LLR is proved to be the best choice, we thus derive another soft forwarding strategy – “Z” forwarding strategy. The main parameter effecting the overall performance in this scheme is the threshold selected to cut the LLR information. We analyze the threshold selection at the relay nodes, and derive the exact ML estimation at the destination node. To circumvent the catastrophic error propagation in digital distributed coding scheme, a distributed soft coding scheme is proposed for the parallel relay networks. The key idea is the exploitation of a rate-1 soft convolutional encoder at each of the parallel relays, to collaboratively form a simple but powerful distributed analog coding scheme. Because of the linearity of the truncated LLR information, a nearly optimal ML decoder is derived for the distributed coding scheme. In the last part, a cooperative transmission scheme for a multi-source single-destination system through superposition modulation is investigated. The source nodes take turns to transmit, and each time, a source “overlays” its new data together with (some or all of) what it overhears from its partner(s), in a way similar to French-braiding the hair. We introduce two subclasses of braid coding, the nonregenerative and the regenerative cases, and, using the pairwise error probability (PEP) as a figure of merit, derive the optimal weight parameters for each one. By exploiting the structure relevance of braid codes with trellis codes, we propose a Viterbi maximum-likelihood (ML) decoding method of linear-complexity for the regenerative case. We also present a soft-iterative joint channel-network decoding. The overall decoding process is divided into the forward message passing and the backward message passing, which makes effective use of the available reliability information from all the received signals. We show that the proposed “braid coding” cooperative scheme benefits not only from the cooperative diversity but also from the bit error rate (BER) performance gain

Next-generation optical access networks based on Orthogonal Frequency Division Multiplexing

Orthogonal Frequency Division Multiplexing (OFDM) is a robust modulation and multiplexing format which is at the base of many present communication standards. The interest of the OFDM application in optical fiber deployments is quite recent. As the next generation of Passive Optical Networks (NG-PONs) is envisioned, targeting greater capacity and user counts, the limitations of TDMA (Time Division Multiplexing Access) approaches to meet the expected increase in requirements becomes evident and therefore new technologies are being explored. Optical OFDMA is an emerging technology which can be a promising candidate. The main goal of this Master Thesis is to study the problem of users multiplexing in access networks, using OFDM as a technology to transmit the user information data. This work has focused in the uplink study of the network, because it is the most challenging part of the network to design. The studies have been conducted both in a theoretical way and also by simulating the targeted environments by means of a fiber optics transmission simulation tool. Virtual Photonics Integrated (VPI) is the software selected for the simulations. This tool is specially designed to simulate optical transmission system environments. The analysis of the Optical Beat Interference, which is a critical impairment in optical carrier multiplexing schemes, is the most important part of the user multiplexing study

Proceedings of the Fall 1995 Advanced Digital Communication Systems

Coordinated Science Laboratory was formerly known as Control Systems Laborator