40 research outputs found

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

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    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

    Review of Recent Trends

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    This work was partially supported by the European Regional Development Fund (FEDER), through the Regional Operational Programme of Centre (CENTRO 2020) of the Portugal 2020 framework, through projects SOCA (CENTRO-01-0145-FEDER-000010) and ORCIP (CENTRO-01-0145-FEDER-022141). Fernando P. Guiomar acknowledges a fellowship from “la Caixa” Foundation (ID100010434), code LCF/BQ/PR20/11770015. Houda Harkat acknowledges the financial support of the Programmatic Financing of the CTS R&D Unit (UIDP/00066/2020).MIMO-OFDM is a key technology and a strong candidate for 5G telecommunication systems. In the literature, there is no convenient survey study that rounds up all the necessary points to be investigated concerning such systems. The current deeper review paper inspects and interprets the state of the art and addresses several research axes related to MIMO-OFDM systems. Two topics have received special attention: MIMO waveforms and MIMO-OFDM channel estimation. The existing MIMO hardware and software innovations, in addition to the MIMO-OFDM equalization techniques, are discussed concisely. In the literature, only a few authors have discussed the MIMO channel estimation and modeling problems for a variety of MIMO systems. However, to the best of our knowledge, there has been until now no review paper specifically discussing the recent works concerning channel estimation and the equalization process for MIMO-OFDM systems. Hence, the current work focuses on analyzing the recently used algorithms in the field, which could be a rich reference for researchers. Moreover, some research perspectives are identified.publishersversionpublishe

    Nonlinear effects in OFDM signal transmission over radio over fibre links

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    The dynamic range limitations that arise from nonlinearity in low-cost and low complexity directly modulated radio over fibre (RoF) links are examined. Statistical non linear models are presented and applied to the case of a RoF link with a low biased laser diode. The effects of distortion on the Error Vector Magnitude (EVM) performance of Orthogonal Frequency-Division Multiplexing (OFDM) signals with different numbers of subcarriers and the connection to the Peak-ta-Average Power Ratio (PAPR) of the signals are investigated. Statistical distributions of the EVM over a large number of transmitted OFDM frames are gained from experimental measurements and analyses of idealized processes. The measurement results show that as the number of subcarriers is reduced the distribution means are not dependent in the expected way on the statistical PAPR of the transmitted OFDM signals. Instead, it is shown that in regions of moderate distortion the median of the EVM is more closely related to the statistical PAPR and to the required back-off for signals with different numbers of subcarriers. Through the employed statistical analysis, the asymptotic convergence of the EVM result to that expected in the idealized case is observed. The results of this analysis also show, how, including the EVM variance in estimations for back-off might be useful, how, in a measurement, the number of transmitted OFDM frames affects the estimated mean EVM. Differing EVM results for subcarriers at the edge and middle of the signal band show that distortion affects the subcarriers at the middle of the band to a stronger degree and that their behaviour is correlated "to the statistical PAPR of the individual signals. Then, a laser model validated against measured performance is designed arid used for simulating the performance of a subcarrier multiplexed 4th generation mobile/wireless RoF transmission system. Predictions indicate that the architecture provides adequate performance in terms of EVM, for different IFFT sizes and modulation levels of up to 256 QAM (at leastL and a combined raw data rate of up to 3.2 Gbps. Based on a 1.5% EVM transmitter requirement with 256 QAM, a system dynamic range of approximately 5.1 dB is predicted. Finally, the use of companding in a directly modulated RaF link, with the aim of reducing the amplification (and isolation) requirements in the remote antenna unit, is demonstrated, quantified through EVM measurements. The resulting improvements in output power are approximately 4.7 dB at an EVM transmitter requirement of 5.6 %, while in terms of the point of onset of distortion-induced EVM increase, the improvement is approximately 7.6 dB

    Study, Measurements and Characterisation of a 5G system using a Mobile Network Operator Testbed

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    The goals for 5G are aggressive. It promises to deliver enhanced end-user experience by offering new applications and services through gigabit speeds, and significantly improved performance and reliability. The enhanced mobile broadband (eMBB) 5G use case, for instance, targets peak data rates as high as 20 Gbps in the downlink (DL) and 10 Gbps in the uplink (UL). While there are different ways to improve data rates, spectrum is at the core of enabling higher mobile broadband data rates. 5G New Radio (NR) specifies new frequency bands below 6 GHz and also extends into mmWave frequencies where more contiguous bandwidth is available for sending lots of data. However, at mmWave frequencies, signals are more susceptible to impairments. Hence, extra consideration is needed to determine test approaches that provide the precision required to accurately evaluate 5G components and devices. Therefore, the aim of the thesis is to provide a deep dive into 5G technology, explore its testing and validation, and thereafter present the OTE (Hellenic Telecommunications Organisation) 5G testbed, including measurement results obtained and its characterisation based on key performance indicators (KPIs)

    Digital Processing for an Analogue Subcarrier Multiplexed Mobile Fronthaul

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    In order to meet the demands of the fifth generation of mobile communication networks (5G), such as very high bit-rates, very low latency and massive machine connectivity, there is a need for a flexible, dynamic, scalable and versatile mobile fronthaul. Current industry fronthaul standards employing sampled radio waveforms for digital transport suffer from spectral inefficiency, making this type of transport impractical for the wide channel bandwidths and multi-antenna systems required by 5G. On the other hand, analogue transport does not suffer from these limitations. It is, however, prone to noise, non-linearity and poor dynamic range. When combined with analogue domain signal aggregation/multiplexing, it also lacks flexibility and scalability, especially at millimetre wave frequencies. Measurements (matched in simulation) of analogue transport at millimetre wave frequencies demonstrate some of these issues. High data rates are demonstrated employing wide bandwidth channels combined using traditional subcarrier multiplexing techniques. However, only a limited number of channels can be multiplexed in this manner, with poor spectral efficiency, as analogue filter limitations do not allow narrow gaps between channels. To this end, over the last few years, there has been significant investigation of analogue transport schemes combined with digital channel aggregation/ de-aggregation (combining/ separating multiple radio waveforms in the digital domain). This work explores such a technique. Digital processing is used at the transmitter to flexibly multiplex a large number of channels in a subcarrier multiplex, without the use of combiners, mixers/ up-converters or Hilbert transforms. Orthogonal Frequency Division Multiplexing (OFDM) - derived Discrete Multi-Tone (DMT) and Single Sideband (SSB) modulated channels are integrated within a single Inverse Fast Fourier Transform (IFFT) operation. Channels or channel groups are mapped systematically into Nyquist zones by using, for example, a single IFFT (for a single 5G mobile numerology) or multiple IFFTs (for multiple 5G mobile numerologies). The analogue transport signal generated in this manner is digitally filtered and band-pass sampled at the receiver such that each corresponding channel (e.g. channels destined to the same radio frequency (RF)/ millimetre wave (mmW) frequency) in the multiplex is presented at the same intermediate frequency, due to the mapping employed at the transmitter. Analogue or digital domain mixers/ down-converters are not required with this technique. Furthermore, each corresponding channel can be readily up-converted to their respective RF/mmW channels with minimal per-signal processing. Measurement results, matched in simulation, for large signal multiplexes with both generic and 5G mobile numerologies show error-vector magnitude performance well within specifications, validating the proposed system. For even larger multiplexes and/or multiplexes residing on a higher IF exceeding the analogue bandwidth and sampling rate specifications of the ADCs at the receiver, the use of a bandwidth-extension device is proposed to extend the mapping to a mapping hierarchy and relax the analogue bandwidth and sampling rate requirements of the ADCs. This allows the receiver to still use digital processing, with only minimal analogue processing, to band-pass sample smaller blocks of channels from the larger multiplex, down to the same intermediate frequency. This ensures that each block of channels is within the analogue bandwidth specification of the ADCs. Performance predictions via simulation (based on a system model matched to the measurements) show promising results for very large multiplexes and large channel bandwidths. The multiplexing technique presented in this work thus allows reductions in per-channel processing for heterogeneous networking (or multi-radio access technologies) and multi-antenna configurations. It also creates a re-configurable and adaptable system based on available processing resources, irrespective of changes to the number of channels and channel groups, channel bandwidths and modulation formats

    Advanced receivers for distributed cooperation in mobile ad hoc networks

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    Mobile ad hoc networks (MANETs) are rapidly deployable wireless communications systems, operating with minimal coordination in order to avoid spectral efficiency losses caused by overhead. Cooperative transmission schemes are attractive for MANETs, but the distributed nature of such protocols comes with an increased level of interference, whose impact is further amplified by the need to push the limits of energy and spectral efficiency. Hence, the impact of interference has to be mitigated through with the use PHY layer signal processing algorithms with reasonable computational complexity. Recent advances in iterative digital receiver design techniques exploit approximate Bayesian inference and derivative message passing techniques to improve the capabilities of well-established turbo detectors. In particular, expectation propagation (EP) is a flexible technique which offers attractive complexity-performance trade-offs in situations where conventional belief propagation is limited by computational complexity. Moreover, thanks to emerging techniques in deep learning, such iterative structures are cast into deep detection networks, where learning the algorithmic hyper-parameters further improves receiver performance. In this thesis, EP-based finite-impulse response decision feedback equalizers are designed, and they achieve significant improvements, especially in high spectral efficiency applications, over more conventional turbo-equalization techniques, while having the advantage of being asymptotically predictable. A framework for designing frequency-domain EP-based receivers is proposed, in order to obtain detection architectures with low computational complexity. This framework is theoretically and numerically analysed with a focus on channel equalization, and then it is also extended to handle detection for time-varying channels and multiple-antenna systems. The design of multiple-user detectors and the impact of channel estimation are also explored to understand the capabilities and limits of this framework. Finally, a finite-length performance prediction method is presented for carrying out link abstraction for the EP-based frequency domain equalizer. The impact of accurate physical layer modelling is evaluated in the context of cooperative broadcasting in tactical MANETs, thanks to a flexible MAC-level simulato

    Channel Estimation and ICI Cancelation in Vehicular Channels of OFDM Wireless Communication Systems

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    Orthogonal frequency division multiplexing (OFDM) scheme increases bandwidth efficiency (BE) of data transmission and eliminates inter symbol interference (ISI). As a result, it has been widely used for wideband communication systems that have been developed during the past two decades and it can be a good candidate for the emerging communication systems such as fifth generation (5G) cellular networks with high carrier frequency and communication systems of high speed vehicles such as high speed trains (HSTs) and supersonic unmanned aircraft vehicles (UAVs). However, the employment of OFDM for those upcoming systems is challenging because of high Doppler shifts. High Doppler shift makes the wideband communication channel to be both frequency selective and time selective, doubly selective (DS), causes inter carrier interference (ICI) and destroys the orthogonality between the subcarriers of OFDM signal. In order to demodulate the signal in OFDM systems and mitigate ICIs, channel state information (CSI) is required. In this work, we deal with channel estimation (CE) and ICI cancellation in DS vehicular channels. The digitized model of the DS channels can be short and dense, or long and sparse. CE methods that perform well for short and dense channels are highly inefficient for long and sparse channels. As a result, for the latter type of channels, we proposed the employment of compressed sensing (CS) based schemes for estimating the channel. In addition, we extended our CE methods for multiple input multiple output (MIMO) scenarios. We evaluated the CE accuracy and data demodulation fidelity, along with the BE and computational complexity of our methods and compared the results with the previous CE procedures in different environments. The simulation results indicate that our proposed CE methods perform considerably better than the conventional CE schemes

    Interference mitigation techniques for optical attocell networks

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    The amount of wireless data traffic has been increasing exponentially. This results in the shortage of radio frequency (RF) spectrum. In order to alleviate the looming spectrum crisis, visible light communication (VLC) has emerged as a supplement to RF techniques. VLC uses light emitting diodes (LEDs) for transmission and employs photodiodes (PDs) for detection. With the advancement of the LED technology, LEDs can now fulfil two functions at the same time: illumination and high-speed wireless communication. In a typical indoor scenario, each single light fixture can act as an access point (AP), and multiple light fixtures in a room can form a cellular wireless network. We refer to this type of networks as ‘optical attocell network’. This thesis focuses on interference mitigation in optical attocell networks. Firstly, the downlink inter-cell interference (ICI) model in optical attocell networks is investigated. The conventional ray-tracing channel model for non-line-of-sight (NLOS) path is studied. Although this model is accurate, it leads to time-consuming computer simulations. In order to reduce the computational complexity, a simplified channel model is proposed to accurately characterise NLOS ICI in optical attocell networks. Using the simplified model, the received signal-to-interference-plus-noise ratio (SINR) distribution in optical attocell networks can be derived in closed-form. This signifies that no Monte Carlo simulation is required to evaluate the user performance in optical attocell networks. Then, with the knowledge of simplified channel model, interference mitigation techniques using angle diversity receivers (ADRs) are investigated in optical attocell networks. An ADR typically consists of multiple PDs with different orientations. By using proper signal combining schemes, ICI in optical attocell networks can be significantly mitigated. Also, a novel double-source cell configuration is proposed. This configuration can further mitigate ICI in optical attocell networks in conjunction with ADRs. Moreover, an analytical framework is proposed to evaluate the user performance in optical attocell networks with ADRs. Finally, optical space division multiple access (SDMA) using angle diversity transmitters is proposed and investigated in optical attocell networks. Optical SDMA can exploit the available bandwidth resource in spatial dimension and mitigate ICI in optical attocell networks. Compared with optical time division multiple access (TDMA), optical SDMA can significantly improve the throughput of optical attocell networks. This improvement scales with the number of LED elements on each angle diversity transmitter. In addition, the upper bound and the lower bound of optical SDMA performance are derived analytically. These bounds can precisely evaluate the performance of optical SDMA systems. Furthermore, optical SDMA is shown to be robust against user position errors, and this makes optical SDMA suitable for practical implementations

    Joint Channel Estimation and Detection for Multi-Carrier MIMO Communications

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    In MIMO OFDM systems, channel estimation and detection are very important. Pilot-based channel estimation using BEMs is widely used for approximating time-frequency variations of doubly-selective channels. BEMs can provide high estimation performance with low computational load. Data-aided channel estimation outperforms the pilot-based estimation. The data-aided estimation iteratively improves estimates using tentative data symbols and corresponding adaptive weights (reweighted channel estimation). These weights are computed assuming Gaussian data errors, which is inapplicable to OFDM. In this thesis, this assumption is however shown to improve the channel estimation performance. The reweighted channel estimation is shown to significantly outperform the unweighted estimation. Most often used mismatched receivers assume perfect channel estimates when detecting data symbols. However, due to limited pilot symbols and data errors, the channel estimates are imperfect, resulting in a degraded detection performance. The optimal receiver without explicit channel estimation significantly outperform mismatched receivers. However, its complexity is high. To reduce the complexity, a receiver that combines mismatched and optimal detection is proposed. The optimal detection is only applied to data symbols unreliably detected by the mismatched detector, identified using weights computed in the reweighted estimator. The channel estimator and the optimal receiver require the knowledge of channel statistics, which are unavailable and difficult to acquire. To overcome this, an adaptive regularization using the cross-validation criterion is introduced, which finds a regularization matrix providing best channel estimates. The proposed receiver has a reduced complexity than the optimal receiver and provides close-to-optimal detection performance without the knowledge of channel PDP. The adaptive regularization is extended to joint estimation of the Doppler-delay spread and channel. The Doppler and delay spread corresponding to the optimal regularization are selected as their estimates. This approach outperforms other known techniques and provides channel estimation performance close to that obtained with perfect channel statistics

    Timing and Carrier Synchronization in Wireless Communication Systems: A Survey and Classification of Research in the Last 5 Years

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    Timing and carrier synchronization is a fundamental requirement for any wireless communication system to work properly. Timing synchronization is the process by which a receiver node determines the correct instants of time at which to sample the incoming signal. Carrier synchronization is the process by which a receiver adapts the frequency and phase of its local carrier oscillator with those of the received signal. In this paper, we survey the literature over the last 5 years (2010–2014) and present a comprehensive literature review and classification of the recent research progress in achieving timing and carrier synchronization in single-input single-output (SISO), multiple-input multiple-output (MIMO), cooperative relaying, and multiuser/multicell interference networks. Considering both single-carrier and multi-carrier communication systems, we survey and categorize the timing and carrier synchronization techniques proposed for the different communication systems focusing on the system model assumptions for synchronization, the synchronization challenges, and the state-of-the-art synchronization solutions and their limitations. Finally, we envision some future research directions
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