Physical-Layer Cooperation in Coded OFDM Relaying Systems

Mobile communication systems nowadays require ever-increasing data rate and coverage of wide areas. One promising approach to achieve this goal is the application of cooperative communications enabled by introducing intermediate nodes known as relays to support the transmission between terminals. By processing and forwarding the receive message at the relays, the path-loss effect between the source and the destination is mitigated. One major limit factor for relay assisted communications is that a relay cannot transmit and receive using the same physical resources. Therefore, a half-duplex constraint is commonly assumed resulting in halved spectral efficiency. To combat this drawback, two-way relaying is introduced, where two sources exchange information with each. On the other hand, due to the physical limitation of the relays, e.g., wireless sensor nodes, it's not possible to implement multiple antennas at one relay, which prohibits the application of multiple-input multiple-output (MIMO) techniques. However, when treating multiple relays as a cluster, a virtual antenna array is formed to perform MIMO techniques in a distributed manner. %This thesis aims at designing efficient one-way and two-way relaying schemes. Specifically, existing schemes from the literature are improved and new schemes are developed with the emphasis on coded orthogonal frequency division multiplexing (OFDM) transmissions. Of special interest is the application of physical-layer network coding (PLNC) for two-phase two-way relaying. In this case, a network coded message is estimated from the superimposed receive signal at the relay using PLNC schemes. The schemes are investigated based on a mutual information analysis and their performance are improved by a newly proposed phase control strategy. Furthermore, performance degradation due to system asynchrony is mitigated depending on different PLNC schemes. When multiple relays are available, novel cooperation schemes allowing information exchange within the relay cluster are proposed that facilitate distributed MIMO reception and transmission. Additionally, smart signaling approaches are presented to enable the cooperation at different levels with the cooperation overhead taken into account adequately in system performance evaluation

Timing and Frequency Synchronization and Channel Estimation in OFDM-based Systems

Orthogonal frequency division multiplexing (OFDM) due to its appealing features, such as robustness against frequency selective fading and simple channel equalization, is adopted in communications systems such as WLAN, WiMAX and DVB. However, OFDM systems are sensitive to synchronization errors caused by timing and frequency offsets. Besides, the OFDM receiver has to perform channel estimation for coherent detection. The goal of this thesis is to investigate new methods for timing and frequency synchronization and channel estimation in OFDM-based systems. First, we investigate new methods for preamble-aided coarse timing estimation in OFDM systems. Two novel timing metrics using high order statistics-based correlation and differential normalization functions are proposed. The performance of the new timing metrics is evaluated using different criteria including class-separability, robustness to the carrier frequency offset, and computational complexity. It is shown that the new timing metrics can considerably increase the class-separability due to their more distinct values at correct and wrong timing instants, and thus give a significantly better detection performance than the existing timing metrics do. Furthermore, a new method for coarse estimation of the start of the frame is proposed, which remarkably reduces the probability of inter-symbol interference (ISI). The improved performances of the new schemes in multipath fading channels are shown by the probabilities of false alarm, missed-detection and ISI obtained through computer simulations. Second, a novel pilot-aided algorithm is proposed for the detection of integer frequency offset (IFO) in OFDM systems. By transforming the IFO into two new integer parameters, the proposed method can largely reduce the number of trial values for the true IFO. The two new integer parameters are detected using two different pilot sequences, a periodic pilot sequence and an aperiodic pilot sequence. It is shown that the new scheme can significantly reduce the computational complexity while achieving almost the same performance as the previous methods do. Third, we propose a method for joint timing and frequency synchronization and channel estimation for OFDM systems that operate in doubly selective channels. Basis expansion modeling (BEM) that captures the time variations of the channel is used to reduce the number of unknown channel parameters. The BEM coefficients along with the timing and frequency offsets are estimated by using a maximum likelihood (ML) approach. An efficient algorithm is then proposed for reducing the computational complexity of the joint estimation. The complexity of the new method is assessed in terms of the number of multiplications. The mean square estimation error of the proposed method is evaluated in comparison with previous methods, indicating a remarkable performance improvement by the new method. Fourth, we present a new scheme for joint estimation of CFO and doubly selective channel in orthogonal frequency division multiplexing systems. In the proposed preamble-aided method, the time-varying channel is represented using BEM. CFO and BEM coefficients are estimated using the principles of particle and Kalman filtering. The performance of the new method in multipath time-varying channels is investigated in comparison with previous schemes. The simulation results indicate a remarkable performance improvement in terms of the mean square errors of CFO and channel estimates. Fifth, a novel algorithm is proposed for timing and frequency synchronization and channel estimation in the uplink of orthogonal frequency division multiple access (OFDMA) systems by considering high-mobility situations and the generalized subcarrier assignment. By using BEM to represent a doubly selective channel, a maximum likelihood (ML) approach is proposed to jointly estimate the timing and frequency offsets of different users as well as the BEM coefficients of the time-varying channels. A space-alternating generalized expectation-maximization algorithm is then employed to transform the maximization problem for all users into several simpler maximization problems for each user. The computational complexity of the new timing and frequency offset estimator is analyzed and its performance in comparison with that of existing methods using the mean square error is evaluated . Finally, two novel approaches for joint CFO and doubly selective channel estimation in the uplink of multiple-input multiple-output orthogonal frequency division multiple access (MIMO-OFDMA) systems are presented. Considering high-mobility situations, where channels change within an OFDMA symbol interval, and the time varying nature of CFOs, BEM is employed to represent the time variations of the channel. Two new approaches are then proposed based on Schmidt Kalman filtering (SKF). The first approach utilizes Schmidt extended Kalman filtering for each user to estimate the CFO and BEM coefficients. The second approach uses Gaussian particle filter along with SKF to estimate the CFO and BEM coefficients of each user. The Bayesian Cramer Rao bound is derived, and performance of the new schemes are evaluated using mean square error. It is demonstrated that the new schemes can significantly improve the mean square error performance in comparison with that of the existing methods

大規模低遅延通信のためのグラントフリー非直交多元接続

電気通信大学202

Physical Layer Techniques for Wireless Communication Systems

The increasing diffusion of mobile devices requiring, everywhere and every time, reliable connections able to support the more common applications, induced in the last years the deployment of telecommunication networks based on technologies capable to respond effectively to the ever-increasing market demand, still a long way off from saturation level. Multicarrier transmission techniques employed in standards for local networks (Wi-Fi) and metropolitan networks (WiMAX) and for many years hot research topic, have been definitely adopted beginning from the fourth generation of cellular systems (LTE). The adoption of multicarrier signaling techniques if on one hand has brought significant advantages to counteract the detrimental effects in environments with particularly harsh propagation channel, on the other hand, has imposed very strict requirements on sensitivity to recovery errors of the carrier frequency offset (CFO) due to the resulting impact on correct signal detection. The main focus of the thesis falls in this area, investigating some aspects relating to synchronization procedures for system based on multicarrier signaling. Particular reference will be made to a network entry procedure for LTE networks and to CFO recovery for OFDM, fltered multitone modulation and direct conversion receivers. Other contributions pertaining to physical layer issues for communication systems, both radio and over acoustic carrier, conclude the thesis

Wireless Channel Modeling and Reconstruction in Massive MIMO Systems

The past few years have witnessed dramatic growth in the number of wirelessly connected devices, which will continue to increase in the future. Following this trend, the capacity of the wireless networks has been enhanced to provide high-quality service to tens of billions of devices. At the same time, in response to the network enhancement, each device unashamedly requests more and more throughput to support high-data-consuming applications such as video calls, high-definition video streaming, and online multiplayer video games. This undoubtedly indicates that the demand for high wireless throughput and numerous new connections will keep increasing in the near future. In addition, the development of new technologies such as virtual/augmented reality, self-driving cars, remote surgery, and other latency-critical applications has caused concern regarding the network response latency. Thus, next-generation wireless networks have to satisfy three main requirements: i) high throughput; ii) simultaneous service to many users; and iii) low latency. Massive multiple-input multiple-output (MIMO) technology, where a base station (BS) equipped with a large antenna array is capable of serving many users simultaneously in the same time-frequency domain, has been developed to mitigate these requirements except the last. However, massive MIMO technology has to overcome the challenges related to the channel estimation (CE) overhead, which inevitably increases the communication latency, to become the absolute leader in the list of promising technologies for next-generation wireless communication. This dissertation focuses on developing solutions that are aimed to mitigate massive MIMO CE challenges. The dissertation consists of three main parts: massive MIMO channel modeling, user localization in massive MIMO networks, and full downlink channel reconstruction. The first part (Chapter 3) discusses an approach for modeling spatially consistent channels in massive MIMO networks. The main focus is put on describing specular reflections of wireless signals from arbitrarily inclined surfaces by taking into account the signals' polarizations and the spatial distributions of massive MIMO antennas. The proposed approach has been validated through simulating signal transmissions in a realistic environment model based on Google Maps. Results show the importance of incorporating a spherical wave propagation model and the consideration of detailed 3D characteristics of the surroundings in the simulation of massive MIMO channels. The second part (Chapter 4) introduces a solution for localizing users in massive MIMO networks. The main focus is on designing algorithms that are capable of estimating the positions of users using only uplink signals by exploring the advantages of the spherical wave propagation model proposed in the first section. The designed localization schemes have been evaluated through both simulation and proof-of-concept experiments. Simulation results show that the schemes can achieve decimeter-level localization accuracy using 64 and more antenna elements for distances up to 300 meters. The proof-of-concept experiment justifies the feasibility of user localization based on the estimation of the spherical shape of the incoming wavefront. The third part (Chapter 5) investigates the problem of reconstructing the full downlink channel from incomplete uplink channel measurements in massive MIMO systems. This problem arises in the next-generation networks, where connected devices have multiple transmitting and non-transmitting antennas. To achieve high throughput, channels for non-transmitting antennas have to be reconstructed. This section presents ARDI, a scheme that builds a bridge between the radio channel and physical signal propagation environment to link spatial information about the non-transmitting antennas with their radio channels. By inferring locations and orientations of the non-transmitting antennas from an incomplete set of uplink channels, ARDI can reconstruct the downlink channels for non-transmitting antennas. The performance evaluation results demonstrate that ARDI is capable of accurately reconstructing full downlink channels when the signal-to-noise ratio is higher than 15dB, thereby expanding the channel capacity of massive MIMO networks

Advanced DSP Algorithms For Modern Wireless Communication Transceivers

A higher network throughput, a minimized delay and reliable communications are some of many goals that wireless communication standards, such as the fifthgeneration (5G) standard and beyond, intend to guarantee for its customers. Hence, many key innovations are currently being proposed and investigated by researchers in the academic and industry circles to fulfill these goals. This dissertation investigates some of the proposed techniques that aim at increasing the spectral efficiency, enhancing the energy efficiency, and enabling low latency wireless communications systems. The contributions lay in the evaluation of the performance of several proposed receiver architectures as well as proposing novel digital signal processing (DSP) algorithms to enhance the performance of radio transceivers. Particularly, the effects of several radio frequency (RF) impairments on the functionality of a new class of wireless transceivers, the full-duplex transceivers, are thoroughly investigated. These transceivers are then designed to operate in a relaying scenario, where relay selection and beamforming are applied in a relaying network to increase its spectral efficiency. The dissertation then investigates the use of greedy algorithms in recovering orthogonal frequency division multiplexing (OFDM) signals by using sparse equalizers, which carry out the equalization in a more efficient manner when the low-complexity single tap OFDM equalizer can no longer recover the received signal due to severe interferences. The proposed sparse equalizers are shown to perform close to conventional optimal and dense equalizers when the OFDM signals are impaired by interferences caused by the insertion of an insufficient cyclic prefix and RF impairments

Cooperative Position and Orientation Estimation with Multi-Mode Antennas

Robotic multi-agent systems are envisioned for planetary exploration and terrestrial applications. Autonomous operation of robots requires estimations of their positions and orientations, which are obtained from the direction-of-arrival (DoA) and the time-of-arrival (ToA) of radio signals exchanged among the agents. In this thesis, we estimate the signal DoA and ToA using a multi-mode antenna (MMA). An MMA is a single antenna element, where multiple orthogonal current modes are excited by different antenna ports. We provide a first study on the use of MMAs for cooperative position and orientation estimation, specifically exploring their DoA estimation capabilities. Assuming the agents of a cooperative network are equipped with MMAs, lower bounds on the achievable position and orientation accuracy are derived. We realize a gap between the theoretical lower bounds and real-world performance of a cooperative radio localization system, which is caused by imperfect antenna and transceiver calibration. Consequentially, we theoretically analyze in-situ antenna calibration, introduce an algorithm for the calibration of arbitrary multiport antennas and show its effectiveness by simulation. To also improve calibration during operation, we propose cooperative simultaneous localization and calibration (SLAC). We show that cooperative SLAC is able to estimate antenna responses and ranging biases of the agents together with their positions and orientations, leading to considerably better position and orientation accuracy. Finally, we validate the results from theory and simulation by experiments with robotic rovers equipped with software-defined radios (SDRs). In conclusion, we show that DoA estimation with an MMA is feasible, and accuracy can be improved by in-situ calibration and SLAC