Precoded Chebyshev-NLMS based pre-distorter for nonlinear LED compensation in NOMA-VLC

Visible light communication (VLC) is one of the main technologies driving the future 5G communication systems due to its ability to support high data rates with low power consumption, thereby facilitating high speed green communications. To further increase the capacity of VLC systems, a technique called non-orthogonal multiple access (NOMA) has been suggested to cater to increasing demand for bandwidth, whereby users' signals are superimposed prior to transmission and detected at each user equipment using successive interference cancellation (SIC). Some recent results on NOMA exist which greatly enhance the achievable capacity as compared to orthogonal multiple access techniques. However, one of the performance-limiting factors affecting VLC systems is the nonlinear characteristics of a light emitting diode (LED). This paper considers the nonlinear LED characteristics in the design of pre-distorter for cognitive radio inspired NOMA in VLC, and proposes singular value decomposition based Chebyshev precoding to improve performance of nonlinear multiple-input multiple output NOMA-VLC. A novel and generalized power allocation strategy is also derived in this work, which is valid even in scenarios when users experience similar channels. Additionally, in this work, analytical upper bounds for the bit error rate of the proposed detector are derived for square $M$-quadrature amplitude modulation.Comment: R. Mitra and V. Bhatia are with Indian Institute of Technology Indore, Indore-453552, India, Email:[email protected], [email protected]. This work was submitted to IEEE Transactions on Communications on October 26, 2016, decisioned on March 3, 2017, and revised on April 25, 2017, and is currently under review in IEEE Transactions on Communication

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

Millimetre-Wave Fibre-Wireless Technologies for 5G Mobile Fronthaul

The unprecedented growth in mobile data traffic, driven primarily by bandwidth rich applications and high definition video is accelerating the development of fifth generation (5G) mobile network. As mobile access network evolves towards centralisation, mobile fronthaul (MFH) architecture becomes essential in providing high capacity, ubiquitous and yet affordable services to subscribers. In order to meet the demand for high data rates in the access, Millimetre-wave (mmWave) has been highlighted as an essential technology in the development of 5G-new radio (5G-NR). In the present MFH architecture which is typically based on common public radio interface (CPRI) protocol, baseband signals are digitised before fibre transmission, featuring high overhead data and stringent synchronisation requirements. A direct application of mmWave 5G-NR to CPRI digital MFH, where signal bandwidth is expected to be up to 1GHz will be challenging, due to the increased complexity of the digitising interface and huge overhead data that will be required for such bandwidth. Alternatively, radio over fibre (RoF) technique can be employed in the transportation of mmWave wireless signals via the MFH link, thereby avoiding the expensive digitisation interface and excessive overhead associated with its implementation. Additionally, mmWave carrier can be realised with the aid of photonic components employed in the RoF link, further reducing the system complexity. However, noise and nonlinearities inherent to analog transmission presents implementation challenges, limiting the system dynamic range. Therefore, it is important to investigate the effects of these impairments in RoF based MFH architecture. This thesis presents extensive research on the impact of noise and nonlinearities on 5G candidate waveforms, in mmWave 5G fibre wireless MFH. Besides orthogonal frequency division multiplexing (OFDM), another radio access technology (RAT) that has received significant attention is filter bank multicarrier (FBMC), particularly due to its high spectral containment and excellent performance in asynchronous transmission. Hence, FBMC waveform is adopted in this work to study the impact of noise and nonlinearities on the mmWave fibre-wireless MFH architecture. Since OFDM is widely deployed and it has been adopted for 5G-NR, the performance of OFDM and FBMC based 5G mmWave RAT in fibre wireless MFH architecture is compared for several implementations and transmission scenarios. To this extent, an end to end transmission testbed is designed and implemented using industry standard VPI Transmission Maker® to investigate five mmWave upconversion techniques. Simulation results show that the impact of noise is higher in FBMC when the signal to-noise (SNR) is low, however, FBMC exhibits better performance compared to OFDM as the SNR improved. More importantly, an evaluation of the contribution of each noise component to the overall system SNR is carried out. It is observed in the investigation that noise contribution from the optical carriers employed in the heterodyne upconversion of intermediate frequency (IF) signals to mmWave frequency dominate the system noise. An adaptive modulation technique is employed to optimise the system throughput based on the received SNR. The throughput of FBMC based system reduced significantly compared to OFDM, due to laser phase noise and chromatic dispersion (CD). Additionally, it is shown that by employing frequency domain averaging technique to enhance the channel estimation (CE), the throughput of FBMC is significantly increased and consequently, a comparable performance is obtained for both waveforms. Furthermore, several coexistence scenarios for multi service transmission are studied, considering OFDM and FBMC based RATs to evaluate the impact inter band interference (IBI), due to power amplifier (PA) nonlinearity on the system performance. The low out of band (OOB) emission in FBMC plays an important role in minimising IBI to adjacent services. Therefore, FBMC requires less guardband in coexistence with multiple services in 5G fibre-wireless MFH. Conversely, OFDM introduced significant OOB to adjacent services requiring large guardband in multi-service coexistence transmission scenario. Finally, a novel transmission scheme is proposed and investigated to simultaneously generate multiple mmWave signals using laser heterodyning mmWave upconversion technique. With appropriate IF and optical frequency plan, several mmWave signals can be realised. Simulation results demonstrate successful simultaneous realisation of 28GHz, 38GHz, and 60GHz mmWave signals

Visible Light Communication (VLC)

Visible light communication (VLC) using light-emitting diodes (LEDs) or laser diodes (LDs) has been envisioned as one of the key enabling technologies for 6G and Internet of Things (IoT) systems, owing to its appealing advantages, including abundant and unregulated spectrum resources, no electromagnetic interference (EMI) radiation and high security. However, despite its many advantages, VLC faces several technical challenges, such as the limited bandwidth and severe nonlinearity of opto-electronic devices, link blockage and user mobility. Therefore, significant efforts are needed from the global VLC community to develop VLC technology further. This Special Issue, “Visible Light Communication (VLC)”, provides an opportunity for global researchers to share their new ideas and cutting-edge techniques to address the above-mentioned challenges. The 16 papers published in this Special Issue represent the fascinating progress of VLC in various contexts, including general indoor and underwater scenarios, and the emerging application of machine learning/artificial intelligence (ML/AI) techniques in VLC

Regularized Neural Detection for One-Bit Massive MIMO Communication Systems

Detection for one-bit massive MIMO systems presents several challenges especially for higher order constellations. Recent advances in both model-based analysis and deep learning frameworks have resulted in several robust one-bit detector designs. Our work builds on the current state-of-the-art gradient descent (GD)-based detector. We introduce two novel contributions in our detector design: (i) We augment each GD iteration with a deep learning-aided regularization step, and (ii) We introduce a novel constellation-based loss function for our regularized DNN detector. This one-bit detection strategy is applied to two different DNN architectures based on algorithm unrolling, namely, a deep unfolded neural network and a deep recurrent neural network. Being trained on multiple randomly sampled channel matrices, these networks are developed as general one-bit detectors. The numerical results show that the combination of the DNN-augmented regularized GD and constellation-based loss function improve the quality of our one-bit detector, especially for higher order M-QAM constellations.Comment: Initially submitted to IEEE TMLCN in October 202

Efficient DSP and Circuit Architectures for Massive MIMO: State-of-the-Art and Future Directions

Massive MIMO is a compelling wireless access concept that relies on the use of an excess number of base-station antennas, relative to the number of active terminals. This technology is a main component of 5G New Radio (NR) and addresses all important requirements of future wireless standards: a great capacity increase, the support of many simultaneous users, and improvement in energy efficiency. Massive MIMO requires the simultaneous processing of signals from many antenna chains, and computational operations on large matrices. The complexity of the digital processing has been viewed as a fundamental obstacle to the feasibility of Massive MIMO in the past. Recent advances on system-algorithm-hardware co-design have led to extremely energy-efficient implementations. These exploit opportunities in deeply-scaled silicon technologies and perform partly distributed processing to cope with the bottlenecks encountered in the interconnection of many signals. For example, prototype ASIC implementations have demonstrated zero-forcing precoding in real time at a 55 mW power consumption (20 MHz bandwidth, 128 antennas, multiplexing of 8 terminals). Coarse and even error-prone digital processing in the antenna paths permits a reduction of consumption with a factor of 2 to 5. This article summarizes the fundamental technical contributions to efficient digital signal processing for Massive MIMO. The opportunities and constraints on operating on low-complexity RF and analog hardware chains are clarified. It illustrates how terminals can benefit from improved energy efficiency. The status of technology and real-life prototypes discussed. Open challenges and directions for future research are suggested.Comment: submitted to IEEE transactions on signal processin

Performance Analysis of Coherent and Noncoherent Modulation under I/Q Imbalance

In-phase/quadrature-phase Imbalance (IQI) is considered a major performance-limiting impairment in direct-conversion transceivers. Its effects become even more pronounced at higher carrier frequencies such as the millimeter-wave frequency bands being considered for 5G systems. In this paper, we quantify the effects of IQI on the performance of different modulation schemes under multipath fading channels. This is realized by developing a general framework for the symbol error rate (SER) analysis of coherent phase shift keying, noncoherent differential phase shift keying and noncoherent frequency shift keying under IQI effects. In this context, the moment generating function of the signal-to-interference-plus-noise-ratio is first derived for both single-carrier and multi-carrier systems suffering from transmitter (TX) IQI only, receiver (RX) IQI only and joint TX/RX IQI. Capitalizing on this, we derive analytic expressions for the SER of the different modulation schemes. These expressions are corroborated by comparisons with corresponding results from computer simulations and they provide insights into the dependence of IQI on the system parameters. We demonstrate that the effects of IQI differ considerably depending on the considered system as some cases of single-carrier transmission appear robust to IQI, whereas multi-carrier systems experiencing IQI at the RX require compensation in order to achieve a reliable communication link

Indoor Visible Light Communication:A Tutorial and Survey

Abstract With the advancement of solid-state devices for lighting, illumination is on the verge of being completely restructured. This revolution comes with numerous advantages and viable opportunities that can transform the world of wireless communications for the better. Solid-state LEDs are rapidly replacing the contemporary incandescent and fluorescent lamps. In addition to their high energy efficiency, LEDs are desirable for their low heat generation, long lifespan, and their capability to switch on and off at an extremely high rate. The ability of switching between different levels of luminous intensity at such a rate has enabled the inception of a new communication technology referred to as visible light communication (VLC). With this technology, the LED lamps are additionally being used for data transmission. This paper provides a tutorial and a survey of VLC in terms of the design, development, and evaluation techniques as well as current challenges and their envisioned solutions. The focus of this paper is mainly directed towards an indoor setup. An overview of VLC, theory of illumination, system receivers, system architecture, and ongoing developments are provided. We further provide some baseline simulation results to give a technical background on the performance of VLC systems. Moreover, we provide the potential of incorporating VLC techniques in the current and upcoming technologies such as fifth-generation (5G), beyond fifth-generation (B5G) wireless communication trends including sixth-generation (6G), and intelligent reflective surfaces (IRSs) among others

Artificial Intelligence Aided Receiver Design for Wireless Communication Systems

Physical layer (PHY) design in the wireless communication field realizes gratifying achievements in the past few decades, especially in the emerging cellular communication systems starting from the first generation to the fifth generation (5G). With the gradual increase in technical requirements of large data processing and end-to-end system optimization, introducing artificial intelligence (AI) in PHY design has cautiously become a trend. A deep neural network (DNN), one of the population techniques of AI, enables the utilization of its ‘learnable’ feature to handle big data and establish a global system model. In this thesis, we exploited this characteristic of DNN as powerful assistance to implement two receiver designs in two different use-cases. We considered a DNN-based joint baseband demodulator and channel decoder (DeModCoder), and a DNN-based joint equalizer, baseband demodulator, and channel decoder (DeTecModCoder) in two single operational blocks, respectively. The multi-label classification (MLC) scheme was equipped to the output of conducted DNN model and hence yielded lower computational complexity than the multiple output classification (MOC) manner. The functional DNN model can be trained offline over a wide range of SNR values under different types of noises, channel fading, etc., and deployed in the real-time application; therefore, the demands of estimation of noise variance and statistical information of underlying noise can be avoided. The simulation performances indicated that compared to the corresponding conventional receiver signal processing schemes, the proposed AI-aided receiver designs have achieved the same bit error rate (BER) with around 3 dB lower SNR