Performance of Hybrid Direct-Sequence Time-Hopping Ultrawide Bandwidth Systems over Nakagami-m Fading Channels

This paper investigates and compares the performance of various ultrawide bandwidth (UWB) systems when communicating over Nakagami-m fading channels. Specifically, the direct-sequence (DS), time-hopping (TH) and hybrid direct-sequence time-hopping (DS-TH) UWB systems are considered. The performance of these UWB systems is studied associated with employing the conventional single-user correlation detector or minimum mean-square error (MMSE) multiuser detector. Our simulation results show that the hybrid DS-TH UWB system may outperform a corresponding pure TH-UWB or pure DS-UWB system in terms of the achievable error performance. Given the total spreading gain of the hybrid DS-TH UWB system, there is an optimal setting of the TH spreading factor and DS spreading factor, which results in the best error performance

Adaptive detection in ultrawide bandwidth wireless communication systems

The main motivation of this thesis is to design low-complexity high-efficiency pulse-based ultrawide bandwidth (UWB) systems with reasonable bit-error-rate (BER) performance. The thesis starts with proposing a new pulse-based UWB system, namely the hybrid direct-sequence time-hopping (DS-TH) UWB system. This novel pulse-based UWB system is capable of inheriting the advantages of both the pure direct-sequence (DS)-UWB and pure time-hopping (TH)-UWB systems, while avoiding their disadvantages. Furthermore, this hybrid DS-TH UWB scheme can be easily converted to the pure DS-UWB or pure TH-UWB scheme. The BER performance of the hybrid DS-TH UWB systems employing either correlation or minimum mean-square error (MMSE) detection is investigated. From our studies it can be found that both the correlation and MMSE detectors have the capability to make use of the multipath diversity. The correlation detector does not have the capability to remove multiuser interference (MUI) and inter-symbol interference (ISI), while the MMSE detector is capable of mitigating efficiently both the ISI and MUI. While for single-user scenario the correlation detector is near-optimum and has low-complexity, it is shown that for multi-user scenarios theMMSE detector must be employed in order to achieve a reasonable BER performance. However, in this case the complexity of the hybrid DS-TH UWB system is found to be extreme. Furthermore, in order to implement MMSE detection, the signature waveforms, delays and complete channel knowledge of all the active users are required to be known by the receiver, which make the MMSE detection impractical. In practical channels obtaining the channel knowledge is highly challenging, since the received UWB signals usually consist of a huge number of resolvable multipaths and the energy conveyed by each resolvable multipath is usually very low.In order to mitigate the above mentioned problems of the MMSE detection, then, in this thesis a range of training-based adaptive detectors are investigated in the context of the hybrid DS-TH UWB systems. In detail, in this thesis a brief introduction to the literature of adaptive detection is first provided, followed by the philosophies of least mean-square (LMS), normalised least-mean squares (NLMS) and recursive least square (RLS) algorithms. In our study decision directed (DD) approaches are also introduced to the adaptive detectors to improve the BER performance and spectral-efficiency of the hybrid DS-TH UWB systems. Our studies show that the complexity of the adaptive LMS and adaptive NLMS detectors may be even lower than that of the conventional correlation detector. For the RLS adaptive detector, our studies show that, if it is initialised properly, it is capable of attaining a faster convergence rate than the LMS and NLMS adaptive detectors. In this case, the RLS adaptive detector requires less number of training bits, and hence provides higher spectral-efficiency than the LMS and NLMS adaptive detectors for the hybrid DS-TH UWB systems. Furthermore, the RLS adaptive detector is more robust and has more degrees of freedom than the LMS and NLMS adaptive detectors. However, the complexity of the RLS adaptive detector is still too high to be implemented in practical UWB systems.In order to further reduce the complexity of the RLS adaptive detector, rank-reduction techniques are introduced. With the aid of reduced-rank techniques, the filter size can be efficiently reduced, which in turn reduces the number of parameters required to be estimated. Consequently, the convergence speed, tracking ability and robustness of the RLS adaptive detector can be improved. In this thesis, three classes of reduced-rank techniques are investigated associated with the RLS adaptive detector, which are derived based on the principles of principal components analysis (PCA), crossspectral metric (CSM) and Taylor polynomial approximation (TPA), respectively. Our study and simulation results show that, given a sufficient rank of the detection subspace on which the RLS adaptive detector is operated, the reduced-rank RLS adaptive detector is capable of achieving a similar BER performance as the corresponding full-rank RLS adaptive detector, while with a detection complexity that is significantly lower than that of the fullrank RLS adaptive detector. Furthermore, our studies shown that the TPA-based reduced-rank RLS adaptive detector constitutes one of the highly efficient detection schemes for the pulse-based UWB systems. The TPA-based reduced-rank RLS adaptive detector is usually capable of attaining the full-rank BER performance with a very low rank, which is typically in the range of 5 ? 8, regardless of the system size in terms of the spreading factor, number of resolvable multipaths and the number of users supported by the UWB systems.Finally, in this thesis we summarise our discoveries and provide discussion on the possible future research issues

Hybrid Digital-to-Analog Beamforming for Millimeter-Wave Systems with High User Density

Millimeter-wave (mm-Wave) systems with hybrid digital-to-analog beamforming (D-A BF) have the potential to fulfill 5G traffic demands. The capacity of mmWave systems is severely limited as each radio frequency (RF) transceiver chain in current base station (BS) architectures support only a particular user. In order to overcome this problem when high density of users are present, a new algorithm is proposed in this paper. This algorithm operates on the principle of selection combining (SC). This algorithm is compared with the state of the art hybrid D-A BF. The simulation results show that our proposed hybrid D-A BF using SC supports higher density of users per RF chain. Furthermore, our proposed algorithm achieves higher capacity than what is achieved by the current hybrid D-A BF systems

Network-Assisted D2D Discovery Method by using Power Control Strategy

Neighbour discovery is an important process in device-to-device (D2D) communications. In cellular networks, D2D discovery signals are multiplexed with cellular signals causing in-band emission interference (IEI). IEI degrades D2D user equipments (DUEs) discovery range and cellular user equipments (CUEs) throughput. In this paper, a new discovery method is proposed by applying power control strategy. In this method, DUEs are arranged into two groups depending on whether the received power of a reference signal sent from the based station (BS) to DUEs is larger than a given threshold. A high received reference signal at a DUE indicates strong IEI which may be caused by the DUE to the BS. Then, Group-1 contains DUEs which cause low IEI while Group-2 contains DUEs which cause severe IEI. A new strategy to mitigate IEI is proposed for Group-2. Firstly, CUEs send scheduling information in predefined blocks. Secondly, DUEs estimate the symbols which are orthogonal to CUE. This will assist DUEs to boost their discovery transmission power, reduce IEI and improve the discovery performance

Capacity Maximisation for Hybrid Digital-to-Analog Beamforming mm-Wave Systems

Millimetre waves (mm-Waves) with massive multiple input and multiple output (MIMO) have the potential to fulfill fifth generation (5G) traffic demands. In this paper, a hybrid digital-to-analog (D-A) precoding system is investigated and a particle swarm optimisation (PSO) based joint D-A precoding optimisation algorithm is proposed. This algorithm maximises the capacity of the hybrid D-A mm-Wave massive MIMO system. The proposed algorithm is compared with three known hybrid D-A precoding algorithms. The analytical and simulation results show that the proposed algorithm achieves higher capacity than the existing hybrid D-A precoding algorithms

Novel Fine-Tuned Attribute Weighted Na\"ive Bayes NLoS Classifier for UWB Positioning

In this paper, we propose a novel Fine-Tuned attribute Weighted Na\"ive Bayes (FT-WNB) classifier to identify the Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) for UltraWide Bandwidth (UWB) signals in an Indoor Positioning System (IPS). The FT-WNB classifier assigns each signal feature a specific weight and fine-tunes its probabilities to address the mismatch between the predicted and actual class. The performance of the FT-WNB classifier is compared with the state-of-the-art Machine Learning (ML) classifiers such as minimum Redundancy Maximum Relevance (mRMR)- $k$-Nearest Neighbour (KNN), Support Vector Machine (SVM), Decision Tree (DT), Na\"ive Bayes (NB), and Neural Network (NN). It is demonstrated that the proposed classifier outperforms other algorithms by achieving a high NLoS classification accuracy of $99.7\%$ with imbalanced data and $99.8\%$ with balanced data. The experimental results indicate that our proposed FT-WNB classifier significantly outperforms the existing state-of-the-art ML methods for LoS and NLoS signals in IPS in the considered scenario

Optimal Photodetector Size for High-Speed Free-Space Optics Receivers

The selection of an optimal photodetector area is closely linked to the attainment of higher data rates in optical wireless communication receivers. If the photodetector area is too large, the channel capacity degrades due to lower modulation bandwidth of the detector. A smaller photodetector maximizes the bandwidth, but minimizes the captured signal power and the subsequent signal-to-noise ratio. Therein lies an opportunity in this trade-off to maximize the channel rate by choosing the optimal photodetector area. In this study, we have optimized the photodetector area in order to maximize the channel capacity of a free-space optical link for a diverse set of communication scenarios. We believe that the study in this paper in general -- and the closed-form solutions derived in this study in particular -- will be helpful to maximize achievable data rates of a wide gamut of optical wireless communication systems: from long range deep space optical links to short range indoor visible light communication systems