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Several efficient low complexity interference management techniques were developed for improving the performance of multiple-input multiple-output (MIMO) networks. Sub-optimal techniques involving optimal antenna selection-aided stream control were proposed for joint optimization of co-channel MIMO links in a space division multiple access (SDMA) network. Results indicated that the use of the SDMA scheme along with partial channel state information at the transmitters significantly reduces the signaling overhead with minimal loss in throughput performance. Next, a mean squared error (MSE) based antenna selection framework was presented for developing low complexity algorithms for finite complexity receivers. These selection algorithms were shown to provide reasonable bit-error rate performance while keeping the overall system complexity low. Furthermore, some new algebraic properties of linear orthogonal space-time block codes (OSTBCs) were utilized to develop a single-stage and minimum MSE optimal detector for two co-channel users employing unity rate real and derived rate-1/2 complex OSTBCs. A sub-optimal space-time interference cancellation (IC) technique was also developed for a spatial-multiplexing link subjected to Alamouti interference. The performance of proposed interference management techniques and their implications for future research are discussed.

We study the two-user multiple-input single-output (MISO) Gaussian interference channel where the transmitters have perfect channel state information and employ single-stream beamforming. The receivers are capable of performing successive interference cancellation, so when the interfering signal is strong enough, it can be decoded, treating the desired signal as noise, and subtracted from the received signal, before the desired signal is decoded. We propose efficient methods to compute the Pareto-optimal rate points and corresponding beamforming vector pairs, by maximizing the rate of one link given the rate of the other link. We do so by splitting the original problem into four subproblems corresponding to the combinations of the receivers' decoding strategies - either decode the interference or treat it as additive noise. We utilize recently proposed parameterizations of the optimal beamforming vectors to equivalently reformulate each subproblem as a quasi-concave problem, which we solve very efficiently either analytically or via scalar numerical optimization. The computational complexity of the proposed methods is several orders-of-magnitude less than the complexity of the state-of-the-art methods. We use the proposed methods to illustrate the effect of the strength and spatial correlation of the channels on the shape of the rate region.

Abstract High radio capacity is one of the main targets in wireless network planning. The characteristics of the broadband radio channel pose serious challenges for achieving this goal. This thesis views the capacity problem from two frameworks. In the first, the effective user capacity in advanced direct sequence wideband code-division multiple-access (DS-CDMA) radio networks is evaluated. Sensitivity to various imperfections in key system parameters is studied. The analysis is based on a mathematical foundation that presents complex signal models and enables evaluation of the performance losses due to parameter estimation errors and multipath fading. The effective number of users supported in a cell is restricted by the multiple access interference (MAI) in the same cell (intracell interference) and overall background noise. The studied wideband CDMA receiver structures comprise conventional rake receivers with both the maximal ratio combining (MRC) and equal gain combining (EGC) schemes that can be supplemented with either linear decorrelating or nonlinear successive cancellation-based multiuser detectors and M-antenna spatial diversity. The second framework focuses on direct sequence spread spectrum-based ultra wideband (UWB) indoor communications. Cochannel interference limited capacity is evaluated against the outage probability criterion in exponentially decaying lognormal multipath fading channels. Distance-dependence and spatial distribution of users is taken into account at different spatial cell configurations. Only moderate complexity partial rake receivers with noncoherent combining are employed. Total interference is composed of interpath, multipath, intracell, and intercell interference contributions. Lognormal sum approximations and simulations are used to evaluate distributions of the desired and interfering signals. The impact of the timing errors at the receiver monopulse correlation is studied. The numerical results for the wideband CDMA framework show that effective user capacity and sensitivity depend critically on the joint impact of nonidealities in system parameters (e.g., channel profile, severity of fading, receiver algorithms). User capacities of the studied multiuser enhanced receivers were more prone to these impairments than those of the simpler single user receivers. The results should be used for network planning and optimization. The numerical results of the UWB framework suggest that, even in the multipath rich channel, the optimal number of rake fingers can be less than half of the significant multipaths. Differences between circular, square, and hexagonal cell models proved to be minor with respect to link distance distributions. The derived link distance statistics are useful tools in the analytic piconet dimensioning and optimization.

In the first part of this dissertation, a novel medium access protocol for the Internet of Thing (IoT) networks is introduced. The Internet of things (IoT), which is the network of physical devices embedded with sensors, actuators, and connectivity, is being accelerated into the mainstream by the emergence of 5G wireless networking. This work presents an uncoordinated non-orthogonal random-access protocol, which is an enhancement to the recently introduced slotted ALOHA- NOMA (SAN) protocol that provides high throughput, while being matched to the low complexity requirements and the sporadic traffic pattern of IoT devices. Under ideal conditions it has been shown that slotted ALOHA-NOMA (SAN), using power- domain orthogonality, can significantly increase the throughput using SIC (Successive Interference Cancellation) to enable correct reception of multiple simultaneous transmitted signals. For this ideal performance, the enhanced SAN receiver adaptively learns the number of active devices (which is not known a priori) using a form of multi-hypothesis testing. For small numbers of simultaneous transmissions, it is shown that there can be substantial throughput gain of 5.5 dB relative to slotted ALOHA (SA) for 0.07 probability of transmission and up to 3 active transmitters. As a further enhancement to SAN protocol, the SAN with beamforming (BF-SAN) protocol was proposed. The BF-SAN protocol uses beamforming to significantly improve the throughput to 1.31 compared with 0.36 in conventional slotted ALOHA when 6 active IoT devices can be successfully separated using 2×2 MIMO and a SIC (Successive Interference Cancellation) receiver with 3 optimum power levels. The simulation results further show that the proposed protocol achieves higher throughput than SAN with a lower average channel access delay. In the second part of this dissertation a novel Machine Learning (ML) approach was applied for proactive mobility management in 5G Virtual Cell (VC) wireless networks. Providing seamless mobility and a uniform user experience, independent of location, is an important challenge for 5G wireless networks. The combination of Coordinated Multipoint (CoMP) networks and Virtual- Cells (VCs) are expected to play an important role in achieving high throughput independent of the mobile’s location by mitigating inter-cell interference and enhancing the cell-edge user throughput. User- specific VCs will distinguish the physical cell from a broader area where the user can roam without the need for handoff, and may communicate with any Base Station (BS) in the VC area. However, this requires rapid decision making for the formation of VCs. In this work, a novel algorithm based on a form of Recurrent Neural Networks (RNNs) called Gated Recurrent Units (GRUs) is used for predicting the triggering condition for forming VCs via enabling Coordinated Multipoint (CoMP) transmission. Simulation results show that based on the sequences of Received Signal Strength (RSS) values of different mobile nodes used for training the RNN, the future RSS values from the closest three BSs can be accurately predicted using GRU, which is then used for making proactive decisions on enabling CoMP transmission and forming VCs. Finally, the work in the last part of this dissertation was directed towards applying Bayesian games for cell selection / user association in 5G Heterogenous networks to achieve the 5G goal of low latency communication. Expanding the cellular ecosystem to support an immense number of connected devices and creating a platform that accommodates a wide range of emerging services of different traffic types and Quality of Service (QoS) metrics are among the 5G’s headline features. One of the key 5G performance metrics is ultra-low latency to enable new delay-sensitive use cases. Some network architectural amendments are proposed to achieve the 5G ultra-low latency objective. With these paradigm shifts in system architecture, it is of cardinal importance to rethink the cell selection / user association process to achieve substantial improvement in system performance over conventional maximum signal-to- interference plus noise ratio (Max-SINR) and Cell Range Expansion (CRE) algorithms employed in Long Term Evolution- Advanced (LTE- Advanced). In this work, a novel Bayesian cell selection / user association algorithm, incorporating the access nodes capabilities and the user equipment (UE) traffic type, is proposed in order to maximize the probability of proper association and consequently enhance the system performance in terms of achieved latency. Simulation results show that Bayesian game approach attains the 5G low end-to-end latency target with a probability exceeding 80%.

Flexible numerology of the physical layer has been introduced in the latest release of 5G new radio (NR) and the baseline waveform generation is chosen to be cyclic-prefix based orthogonal frequency division multiplexing (CP-OFDM). Thanks to the narrow subcarrier spacing and low complexity one tap equalization (EQ) of OFDM, it suits well to time-dispersive channels. For the upcoming 5G and beyond use-case scenarios, it is foreseen that the users might experience high mobility conditions. While the frame structure of the 5G NR is designed for long coherence times, the synchronization and channel estimation (CE) procedures are not fully and reliably covered for diverse applications. The research on alternative multi-carrier waveforms has brought up valuable results in terms of spectral efficiency, applications coexistence and flexibility. Nevertheless, the receiver design becomes more challenging for multiple-input multiple-output (MIMO) non-orthogonal multi-carriers because the receiver must deal with multiple dimensions of interference. This thesis aims to deliver accurate pilot-aided estimations of the wireless channel for coherent detection. Considering a MIMO non-orthogonal multi-carrier, e.g. generalized frequency division multiplexing (GFDM), we initially derive the classical and Bayesian estimators for rich multi-path fading channels, where we theoretically assess the choice of pilot design. Moreover, the well time- and frequency-localization of the pilots in non-orthogonal multi-carriers allows to reuse their energy from cyclic-prefix (CP). Taking advantage of this feature, we derive an iterative approach for joint CE and EQ of MIMO systems. Furthermore, exploiting the block-circularity of GFDM, we comprehensively analyze the complexity aspects, and propose a solution for low complexity implementation. Assuming very high mobility use-cases where the channel varies within the symbol duration, further considerations, particularly the channel coherence time must be taken into account. A promising candidate that is fully independent of the multi-carrier choice is unique word (UW) transmission, where the CP of random nature is replaced by a deterministic sequence. This feature, allows per-block synchronization and channel estimation for robust transmission over extremely doubly-dispersive channels. In this thesis, we propose a novel approach to extend the UW-based physical layer design to MIMO systems and we provide an in-depth study of their out-of-band emission, synchronization, CE and EQ procedures. Via theoretical derivations and simulation results, and comparisons with respect to the state-of-the-art CP-OFDM systems, we show that the proposed UW-based frame design facilitates robust transmission over extremely doubly-dispersive channels.:1 Introduction 1 1.1 Multi-Carrier Waveforms 1 1.2 MIMO Systems 3 1.3 Contributions and Thesis Structure 4 1.4 Notations 6 2 State-of-the-art and Fundamentals 9 2.1 Linear Systems and Problem Statement 9 2.2 GFDM Modulation 11 2.3 MIMO Wireless Channel 12 2.4 Classical and Bayesian Channel Estimation in MIMO OFDM Systems 15 2.5 UW-Based Transmission in SISO Systems 17 2.6 Summary 19 3 Channel Estimation for MIMO Non-Orthogonal Waveforms 21 3.1 Classical and Bayesian Channel Estimation in MIMO GFDM Systems 22 3.1.1 MIMO LS Channel Estimation 23 3.1.2 MIMO LMMSE Channel Estimation 24 3.1.3 Simulation Results 25 3.2 Basic Pilot Designs for GFDM Channel Estimation 29 3.2.1 LS/HM Channel Estimation 31 3.2.2 LMMSE Channel Estimation for GFDM 32 3.2.3 Error Characterization 33 3.2.4 Simulation Results 36 3.3 Interference-Free Pilot Insertion for MIMO GFDM Channel Estimation 39 3.3.1 Interference-Free Pilot Insertion 39 3.3.2 Pilot Observation 40 3.3.3 Complexity 41 3.3.4 Simulation Results 41 3.4 Bayesian Pilot- and CP-aided Channel Estimation in MIMO NonOrthogonal Multi-Carriers 45 3.4.1 Review on System Model 46 3.4.2 Single-Input-Single-Output Systems 47 3.4.3 Extension to MIMO 50 3.4.4 Application to GFDM 51 3.4.5 Joint Channel Estimation and Equalization via LMMSE Parallel Interference Cancellation 57 3.4.6 Complexity Analysis 61 3.4.7 Simulation Results 61 3.5 Pilot- and CP-aided Channel Estimation in Time-Varying Scenarios 67 3.5.1 Adaptive Filtering based on Wiener-Hopf Approac 68 3.5.2 Simulation Results 69 3.6 Summary 72 4 Design of UW-Based Transmission for MIMO Multi-Carriers 73 4.1 Frame Design, Efficiency and Overhead Analysis 74 4.1.1 Illustrative Scenario 74 4.1.2 CP vs. UW Efficiency Analysis 76 4.1.3 Numerical Results 77 4.2 Sequences for UW and OOB Radiation 78 4.2.1 Orthogonal Polyphase Sequences 79 4.2.2 Waveform Engineering for UW Sequences combined with GFDM 79 4.2.3 Simulation Results for OOB Emission of UW-GFDM 81 4.3 Synchronization 82 4.3.1 Transmission over a Centralized MIMO Wireless Channel 82 4.3.2 Coarse Time Acquisition 83 4.3.3 CFO Estimation and Removal 85 4.3.4 Fine Time Acquisition 86 4.3.5 Simulation Results 88 4.4 Channel Estimation 92 4.4.1 MIMO UW-based LMMSE CE 92 4.4.2 Adaptive Filtering 93 4.4.3 Circular UW Transmission 94 4.4.4 Simulation Results 95 4.5 Equalization with Imperfect Channel Knowledge 96 4.5.1 UW-Free Equalization 97 4.5.2 Simulation Results 99 4.6 Summary 102 5 Conclusions and Perspectives 103 5.1 Main Outcomes in Short 103 5.2 Open Challenges 105 A Complementary Materials 107 A.1 Linear Algebra Identities 107 A.2 Proof of lower triangular Toeplitz channel matrix being defective 108 A.3 Calculation of noise-plus-interference covariance matrix for Pilot- and CPaided CE 108 A.4 Bock diagonalization of the effective channel for GFDM 109 A.5 Detailed complexity analysis of Sec. 3.4 109 A.6 CRLB derivations for the pdf (4.24) 113 A.7 Proof that (4.45) emulates a circular CIR at the receiver 114

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第20741号 / 情博第655号 / 新制||情||113(附属図書館) / 京都大学大学院情報学研究科通信情報システム専攻 / (主査)教授 原田 博司, 教授 守倉 正博, 教授 大木 英司 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Previous approach for narrowband interference cancellation based on compressed sensing (CS) in wideband receivers uses orthogonal projections to project away from the interference. This is not effective in the presence of nonlinear LNA (low noise amplifier) and finite bit ADCs (analog-to-digital converters) due to the fact that the nonidealities present will result in irresolvable intermodulation components and corrupt the signal reconstruction. Cancelling out the interferer before reaching the LNA thus becomes very important. A CS measurement matrix with randomly placed zeros in the frequency domain helps in this regard by removing the effect of interference when the signal measurements are performed before the LNA. Using this idea, under much idealized hardware assumptions impressive performance is obtained. The use of binary sequences which makes the hardware implementation simplistic is investigated in this thesis. Searching sequences with many spectral nulls turns out to be nontrivial. A theoretical approach for estimating probability of nulls is provided to reduce significant computational effort in the search and is shown to be close to actual search iterations. The use of real binary sequences (generated using ideal switches) obtained through the search does not do better compared to the orthogonal projection method in the presence of nonlinear LNA.

Interference limits the throughput of modern wireless communication networks, and thus the successful mitigation of interference can have a significant impact on network performance. Successive interference cancellation (SIC) has emerged as a promising physical layer method, where multiple packets received simultaneously need not be treated as a ``collision'' requiring retransmission; rather, under certain conditions, all of the packets can be decoded. Obviously, using SIC can thus serve as an important design element that can provide higher performance for the network. However, it also requires a rethinking of the way that traditional routing and scheduling algorithms, which are designed for a traditional physical layer, are developed. In order to consider routing and scheduling over a physical layer employing SIC, some tools such as the oft-employed conflict graph need to be modified. In particular, a notion of links interfering with other links ``indirectly'' is required, and this issue has been ignored in many past works. Therefore, considering the dependencies and interferences between links, a joint routing and scheduling algorithm that employs an understanding of the SIC that will be employed at the physical layer is presented and shown to surpass previous algorithms. We know that the maximum throughput scheduling problem is NP-hard. On the other hand, even if we can reach maximum throughput scheduling, while being throughput efficient, it can result in highly unfair rates among the users. Hence, proportional fairness is developed in the proposed algorithm.

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