End-to-End Learning of OFDM Waveforms with PAPR and ACLR Constraints

Orthogonal frequency-division multiplexing (OFDM) is widely used in modern wireless networks thanks to its efficient handling of multipath environment. However, it suffers from a poor peak-to-average power ratio (PAPR) which requires a large power backoff, degrading the power amplifier (PA) efficiency. In this work, we propose to use a neural network (NN) at the transmitter to learn a high-dimensional modulation scheme allowing to control the PAPR and adjacent channel leakage ratio (ACLR). On the receiver side, a NN-based receiver is implemented to carry out demapping of the transmitted bits. The two NNs operate on top of OFDM, and are jointly optimized in and end-to-end manner using a training algorithm that enforces constraints on the PAPR and ACLR. Simulation results show that the learned waveforms enable higher information rates than a tone reservation baseline, while satisfying predefined PAPR and ACLR targets

Peak-to-Average Power Ratio Reduction of DOCSIS 3.1 Downstream Signals

Tone reservation (TR) is an attractive and widely used method for peak-to-average power ratio (PAPR) reduction of orthogonal frequency division multiplexing (OFDM) signals, where both transmitter and receiver agree upon a number of subcarriers or tones to be reserved to generate a peak canceling signal that can reduce the peak power of the transmitted signals. The tones are selected to be mutually exclusive with the tones used for data transmission, which allows the receiver to extract the data symbols without distortions. This thesis presents two novel PAPR reduction algorithms for OFDM signals based on the TR principle, which do not distort the transmitted signals. The first proposed algorithm is performed in the time domain, whereas the second algorithm is a new clipping-and-filtering method. Both algorithms consist of two stages. The first stage, which is done off-line, creates a set of canceling signals based on the settings of the OFDM system. In particular, these signals are constructed to cancel signals at different levels of maximum instantaneous power that are above a predefined threshold. The second stage, which is online and iterative, reduces the signal peaks by using the canceling signals constructed in the first stage. The precalculated canceling signals can be updated when different tone sets are selected for data transmission, accommodating many practical applications. Simulation results show that the proposed algorithms achieve slightly better PAPR reduction performance than the conventional algorithms. Moreover, such performance is achieved with much lower computational complexity in terms of numbers of multiplications and additions per iteration. Among the two proposed algorithms, the time-domain algorithm gives the best peak reduction performance but the clipping-and-filtering algorithm requires considerably less number of multiplications per iteration and can be efficiently implemented using the fast Fourier transform (FFT)/inverse fast Fourier transform (IFFT) structure

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

PAPR Reduction Method based on In-phase/Quadrature Data Symbol Components in MIMO-OFDM Systems

To overcome unpredictable spikes in the peak-toaverage power ratio (PAPR) in the presence of an orthogonal frequency-division multiplexing (OFDM) for multi-input-multioutput (MIMO) systems, implementation of a new SLM scheme is presented in this paper, which is extended from our previous study of IQ-SLM in SISO-OFDM system. In each transmit antenna, both real and imaginary parts of the base-band data symbol were modified independently using a corresponding phase element within a commonly generated phase vector, instead of modifying the complex data symbol as a single component. After applying an inverse fast Fourier transform (IFFT) for the real, imaginary, and original base-band vectors, the minimum PAPR component was observed. Therefore, the phase vector that introduced the minimal PAPR was considered to convert the original data block for transmission. This technique is called the In-phase/Quadrature-SLM (IQ-SLM) scheme. In this proposal, only U phase vectors were generated to treat all Nt data blocks, simultaneously, unlike the conventional MIMO-SLM techniques which generate UNt candidate phase blocks. The thing which, in turn, can be considered as a further computational complexity reduction, specifically in data-phase conversion stages. As a result, in terms of the complementary cumulative distribution function of PAPR performance(CCDF-PAPR), the proposal achieved a greater decibel reduction than conventional SLM methods such as dSLM, oSLM, and sSLM, at different subcarrier lengths N, candidate phase vectors U, transmit antennas Nt. Also, it shows a comparable BER performances over the dSLM scheme referencing to the theoretical curves, in the case where Nt ≤ Nr for both zero-forcing (ZF) and ZF with vertical Bell laboratories layered space-time (V-BLAST) detector