Performance Analysis and Enhancement of Multiband OFDM for UWB Communications

In this paper, we analyze the frequency-hopping orthogonal frequency-division multiplexing (OFDM) system known as Multiband OFDM for high-rate wireless personal area networks (WPANs) based on ultra-wideband (UWB) transmission. Besides considering the standard, we also propose and study system performance enhancements through the application of Turbo and Repeat-Accumulate (RA) codes, as well as OFDM bit-loading. Our methodology consists of (a) a study of the channel model developed under IEEE 802.15 for UWB from a frequency-domain perspective suited for OFDM transmission, (b) development and quantification of appropriate information-theoretic performance measures, (c) comparison of these measures with simulation results for the Multiband OFDM standard proposal as well as our proposed extensions, and (d) the consideration of the influence of practical, imperfect channel estimation on the performance. We find that the current Multiband OFDM standard sufficiently exploits the frequency selectivity of the UWB channel, and that the system performs in the vicinity of the channel cutoff rate. Turbo codes and a reduced-complexity clustered bit-loading algorithm improve the system power efficiency by over 6 dB at a data rate of 480 Mbps.Comment: 32 pages, 10 figures, 1 table. Submitted to the IEEE Transactions on Wireless Communications (Sep. 28, 2005). Minor revisions based on reviewers' comments (June 23, 2006

Hybrid ARQ with parallel and serial concatenated convolutional codes for next generation wireless communications

This research focuses on evaluating the currently used FEC encoding-decoding schemes and improving the performance of error control systems by incorporating these schemes in a hybrid FEC-ARQ environment. Beginning with an overview of wireless communications and the various ARQ protocols, the thesis provides an in-depth explanation of convolutional encoding and Viterbi decoding, turbo (PCCC) and serial concatenated convolutional (SCCC) encoding with their respective MAP decoding strategies.;A type-II hybrid ARQ scheme with SCCCs is proposed for the first time and is a major contribution of this thesis. A vast improvement is seen in the BER performance of the successive individual FEC schemes discussed above. Also, very high throughputs can be achieved when these schemes are incorporated in an adaptive type-II hybrid ARQ system.;Finally, the thesis discusses the equivalence of the PCCCs and the SCCCs and proposes a technique to generate a hybrid code using both schemes

Probabilistic Shaping for Finite Blocklengths: Distribution Matching and Sphere Shaping

In this paper, we provide for the first time a systematic comparison of distribution matching (DM) and sphere shaping (SpSh) algorithms for short blocklength probabilistic amplitude shaping. For asymptotically large blocklengths, constant composition distribution matching (CCDM) is known to generate the target capacity-achieving distribution. As the blocklength decreases, however, the resulting rate loss diminishes the efficiency of CCDM. We claim that for such short blocklengths and over the additive white Gaussian channel (AWGN), the objective of shaping should be reformulated as obtaining the most energy-efficient signal space for a given rate (rather than matching distributions). In light of this interpretation, multiset-partition DM (MPDM), enumerative sphere shaping (ESS) and shell mapping (SM), are reviewed as energy-efficient shaping techniques. Numerical results show that MPDM and SpSh have smaller rate losses than CCDM. SpSh--whose sole objective is to maximize the energy efficiency--is shown to have the minimum rate loss amongst all. We provide simulation results of the end-to-end decoding performance showing that up to 1 dB improvement in power efficiency over uniform signaling can be obtained with MPDM and SpSh at blocklengths around 200. Finally, we present a discussion on the complexity of these algorithms from the perspective of latency, storage and computations.Comment: 18 pages, 10 figure

Iterative decoding and detection for physical layer network coding

PhD ThesisWireless networks comprising multiple relays are very common and it is important that all users are able to exchange messages via relays in the shortest possible time. A promising technique to achieve this is physical layer network coding (PNC), where the time taken to exchange messages between users is achieved by exploiting the interference at the relay due to the multiple incoming signals from the users. At the relay, the interference is demapped to a binary sequence representing the exclusive-OR of both users’ messages. The time to exchange messages is reduced because the relay broadcasts the network coded message to both users, who can then acquire the desired message by applying the exclusive-OR of their original message with the network coded message. However, although PNC can increase throughput it is at the expense of performance degradation due to errors resulting from the demapping of the interference to bits. A number of papers in the literature have investigated PNC with an iterative channel coding scheme in order to improve performance. However, in this thesis the performance of PNC is investigated for end-to-end (E2E) the three most common iterative coding schemes: turbo codes, low-density parity-check (LDPC) codes and trellis bit-interleaved coded modulation with iterative decoding (BICM-ID). It is well known that in most scenarios turbo and LDPC codes perform similarly and can achieve near-Shannon limit performance, whereas BICM-ID does not perform quite as well but has a lower complexity. However, the results in this thesis show that on a two-way relay channel (TWRC) employing PNC, LDPC codes do not perform well and BICM-ID actually outperforms them while also performing comparably with turbo codes. Also presented in this thesis is an extrinsic information transfer (ExIT) chart analysis of the iterative decoders for each coding scheme, which is used to explain this surprising result. Another problem arising from the use of PNC is the transfer of reliable information from the received signal at the relay to the destination nodes. The demapping of the interference to binary bits means that reliability information about the received signal is lost and this results in a significant degradation in performance when applying soft-decision decoding at the destination nodes. This thesis proposes the use of traditional angle modulation (frequency modulation (FM) and phase modulation (PM)) when broadcasting from the relay, where the real and imaginary parts of the complex received symbols at the relay modulate the frequency or phase of a carrier signal, while maintaining a constant envelope. This is important since the complex received values at the relay are more likely to be centred around zero and it undesirable to transmit long sequences of low values due to potential synchronisation problems at the destination nodes. Furthermore, the complex received values, obtained after angle demodulation, are used to derive more reliable log-likelihood ratios (LLRs) of the received symbols at the destination nodes and consequently improve the performance of the iterative decoders for each coding scheme compared with conventionally coded PNC. This thesis makes several important contributions: investigating the performance of different iterative channel coding schemes combined with PNC, presenting an analysis of the behaviour of different iterative decoding algorithms when PNC is employed using ExIT charts, and proposing the use of angle modulation at the relay to transfer reliable information to the destination nodes to improve the performance of the iterative decoding algorithms. The results from this thesis will also be useful for future research projects in the areas of PNC that are currently being addressed, such as synchronisation techniques and receiver design.Iraqi Ministry of Higher Education and Scientific Research

Spectrally and Energy Efficient Wireless Communications: Signal and System Design, Mathematical Modelling and Optimisation

This thesis explores engineering studies and designs aiming to meeting the requirements of enhancing capacity and energy efficiency for next generation communication networks. Challenges of spectrum scarcity and energy constraints are addressed and new technologies are proposed, analytically investigated and examined. The thesis commences by reviewing studies on spectrally and energy-efficient techniques, with a special focus on non-orthogonal multicarrier modulation, particularly spectrally efficient frequency division multiplexing (SEFDM). Rigorous theoretical and mathematical modelling studies of SEFDM are presented. Moreover, to address the potential application of SEFDM under the 5th generation new radio (5G NR) heterogeneous numerologies, simulation-based studies of SEFDM coexisting with orthogonal frequency division multiplexing (OFDM) are conducted. New signal formats and corresponding transceiver structure are designed, using a Hilbert transform filter pair for shaping pulses. Detailed modelling and numerical investigations show that the proposed signal doubles spectral efficiency without performance degradation, with studies of two signal formats; uncoded narrow-band internet of things (NB-IoT) signals and unframed turbo coded multi-carrier signals. The thesis also considers using constellation shaping techniques and SEFDM for capacity enhancement in 5G system. Probabilistic shaping for SEFDM is proposed and modelled to show both transmission energy reduction and bandwidth saving with advantageous flexibility for data rate adaptation. Expanding on constellation shaping to improve performance further, a comparative study of multidimensional modulation techniques is carried out. A four-dimensional signal, with better noise immunity is investigated, for which metaheuristic optimisation algorithms are studied, developed, and conducted to optimise bit-to-symbol mapping. Finally, a specially designed machine learning technique for signal and system design in physical layer communications is proposed, utilising the application of autoencoder-based end-to-end learning. Multidimensional signal modulation with multidimensional constellation shaping is proposed and optimised by using machine learning techniques, demonstrating significant improvement in spectral and energy efficiencies