A novel mobile communication system using Pulse Position based Chirp Spread Spectrum modulation

The paper presents a new mobile communication system based on Chirp Spread Spectrum (CSS) transmission. The downlink modulation scheme is extended with Pulse Position Modulation (PPM) to carry data for multiple mobile terminals simultaneously. The described novel mechanism ensures reliable and robust communication between the parties, especially for terminals moving with high speeds or at long range. Furthermore, the proposed system take care of the uplink communication as well, where Closed-Loop Power Control (CLPC) is applied to handle the near-far problem and improve the performance of the system. Based on the attributes of the proposed system the application area covers sensor networks, IoT applications and Industry 4.0 as general field of LPWAN, however, mobility of terminals also considered.Analytical investigations for downlink communication are described focusing on the instantaneous symbol-error rate and average SER in Rayleigh fading channel. The results show that the proposed Pulse Position based Chirp Spread Spectrum technique for Multiple Access (shortly PP-CSS-MA) allows higher data rates that is used for the multiple access feature. In addition, numerical results are presented as well, and they point out the benefits of the applied CLPC mechanism. Finally, considerations regarding to the implementation of the proposed communication system are described

Near far resistant detection for CDMA personal communication systems.

The growth of Personal Communications, the keyword of the 90s, has already the signs of a technological revolution. The foundations of this revolution are currently set through the standardization of the Universal Mobile Telecommunication System (UMTS), a communication system with synergistic terrestrial and satellite segments. The main characteristic of the UMTS radio interface, is the provision of ISDN services. Services with higher than voice data rates require more spectrum, thus techniques that utilize spectrum as efficiently as possible are currently at the forefront of the research community interests. Two of the most spectrally efficient multiple access technologies, namely. Code Division Multiple Access (CDMA) and Time Division Multiple Access (TDMA) concentrate the efforts of the European telecommunity.This thesis addresses problems and. proposes solutions for CDMA systems that must comply with the UMTS requirements. Prompted by Viterbi's call for further extending the potential of CDMA through signal processing at the receiving end, we propose new Minimum Mean Square Error receiver architectures. MMSE detection schemes offer significant advantages compared to the conventional correlation based receivers as they are NEar FAr Resistant (NEFAR) over a wide range of interfering power levels. The NEFAR characteristic of these detectors reduces considerably the requirements of the power control loops currently found in commercial CDMA systems. MMSE detectors are also found, to have significant performance gains over other well established interference cancellation techniques like the decorrelating detector, especially in heavily loaded system conditions. The implementation architecture of MMSE receivers can be either Multiple-Input Multiple Output (MIMO) or Single-Input Single-Output. The later offers not only complexity that is comparable to the conventional detector, but also has the inherent advantage of employing adaptive algorithms which can be used to provide both the dispreading and the interference cancellation function, without the knowledge of the codes of interfering users. Furthermore, in multipath fading channels, adaptive MMSE detectors can exploit the multipath diversity acting as RAKE combiners. The later ability is distinctive to MMSE based receivers, and it is achieved in an autonomous fashion, without the knowledge of the multipath intensity profile. The communicator achieves its performance objectives by the synergy of the signal processor and the channel decoder. According to the propositions of this thesis, the form of the signal processor needs to be changed, in order to exploit the horizons of spread spectrum signaling. However, maximum likelihood channel decoding algorithms need not change. It is the way that these algorithms are utilized that needs to be revis ed. In this respect, we identify three major utilization scenarios and an attempt is made to quantify which of the three best matches the requirements of a UMTS oriented CDMA radio interface. Based on our findings, channel coding can be used as a mapping technique from the information bit to a more ''intelligent" chip, matching the ''intelligence" of the signal processor

Inter-carrier interference suppression in orthogonal frequency division multiple access (OFDMA) systems uplink

Ph.DDOCTOR OF PHILOSOPH

A novel mobile communication system using Pulse Position based Chirp Spread Spectrum modulation

The paper presents a new mobile communication system based on Chirp Spread Spectrum (CSS) transmission. The downlink modulation scheme is extended with Pulse Position Modulation (PPM) to carry data for multiple mobile terminals simultaneously. The described novel mechanism ensures reliable and robust communication between the parties, especially for terminals moving with high speeds or at long range. Furthermore, the proposed system take care of the uplink communication as well, where Closed-Loop Power Control (CLPC) is applied to handle the near-far problem and improve the performance of the system. Based on the attributes of the proposed system the application area covers sensor networks, IoT applications and Industry 4.0 as general field of LPWAN, however, mobility of terminals also considered.Analytical investigations for downlink communication are described focusing on the instantaneous symbol-error rate and average SER in Rayleigh fading channel. The results show that the proposed Pulse Position based Chirp Spread Spectrum technique for Multiple Access (shortly PP-CSS-MA) allows higher data rates that is used for the multiple access feature. In addition, numerical results are presented as well, and they point out the benefits of the applied CLPC mechanism. Finally, considerations regarding to the implementation of the proposed communication system are described

Deep Learning Designs for Physical Layer Communications

Wireless communication systems and their underlying technologies have undergone unprecedented advances over the last two decades to assuage the ever-increasing demands for various applications and emerging technologies. However, the traditional signal processing schemes and algorithms for wireless communications cannot handle the upsurging complexity associated with fifth-generation (5G) and beyond communication systems due to network expansion, new emerging technologies, high data rate, and the ever-increasing demands for low latency. This thesis extends the traditional downlink transmission schemes to deep learning-based precoding and detection techniques that are hardware-efficient and of lower complexity than the current state-of-the-art. The thesis focuses on: precoding/beamforming in massive multiple-inputs-multiple-outputs (MIMO), signal detection and lightweight neural network (NN) architectures for precoder and decoder designs. We introduce a learning-based precoder design via constructive interference (CI) that performs the precoding on a symbol-by-symbol basis. Instead of conventionally training a NN without considering the specifics of the optimisation objective, we unfold a power minimisation symbol level precoding (SLP) formulation based on the interior-point-method (IPM) proximal ‘log’ barrier function. Furthermore, we propose a concept of NN compression, where the weights are quantised to lower numerical precision formats based on binary and ternary quantisations. We further introduce a stochastic quantisation technique, where parts of the NN weight matrix are quantised while the remaining is not. Finally, we propose a systematic complexity scaling of deep neural network (DNN) based MIMO detectors. The model uses a fraction of the DNN inputs by scaling their values through weights that follow monotonically non-increasing functions. Furthermore, we investigate performance complexity tradeoffs via regularisation constraints on the layer weights such that, at inference, parts of network layers can be removed with minimal impact on the detection accuracy. Simulation results show that our proposed learning-based techniques offer better complexity-vs-BER (bit-error-rate) and complexity-vs-transmit power performances compared to the state-of-the-art MIMO detection and precoding techniques

A guide to wireless networking by light

The lack of wireless spectrum in the radio frequency bands has led to a rapid growth in research in wireless networking using light, known as LiFi (light fidelity). In this paper an overview of the subsystems, challenges and techniques required to achieve this is presented