고속 이동 환경에서 대규모 다중안테나 시스템에 관한 연구

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 전기·정보공학부, 2020. 8. 이용환.Advanced cellular communication systems may obtain high array gain by employing massive multi-input multi-output (m-MIMO) systems, which may require accurate channel state information (CSI). When users are in high mobility, it may not be easy to get accurate CSI. When we transmit signal to users in high mobility, we may experience serious performance loss due to the inaccuracy of outdated CSI, associated with so-called channel aging effect. This problem may be alleviated by exploiting channel correlation matrix (CCM) in spatial domain. However, it may require an additional process for the estimation of CCM, which may require high signaling overhead in m-MIMO environments. In this dissertation, we consider signal transmission to multiple users in high mobility in m-MIMO environments. We consider the estimation of CSI with reduced signaling overhead. The signaling overhead for the CSI estimation is a challenging issue in m-MIMO environments. We may reduce the signaling overhead for the CSI estimation by using pilot signal transmitted by means of beamforming with a weight determined by eigenvectors of CCM. To this end, we need to estimate the CCM, which may still require large signaling overhead. We consider the estimation of CCM with antennas in a uniform linear array (ULA). Since pairs of antennas with an equal distance may experience spatial channel correlation similar to each other in ULA antenna environments, we may jointly estimate the spatial channel correlation. We estimate the mean-square error (MSE) of elements of estimated CCM and then discard the elements whose MSE is higher than a reference value for the improvement of CCM estimation. We may estimate the CSI from the estimated CCM with reduced signaling overhead. We consider signal transmission robust to the presence of channel aging effect. Users in different mobility may differently experience the channel aging effect. This means that they may differently suffer from transmission performance loss. To alleviate this problem, we transmit signal to maximize the average signal-to-leakage-plus-noise ratio, making it possible to individually handle the channel aging effect. We consider the signal transmission to the eigen-direction of a linear combination of CSI and CCM. Analyzing the transmission performance in terms of signal-to-interference-plus-noise ratio, we control the transmit power by using an iterative water-filling technique. Finally, we consider the allocation of transmission resource in the presence of channel aging effect. We design a sub-optimal greedy algorithm that allocates the transmission resource to maximize the sum-rate in the presence of channel aging effect. We may estimate the sum-rate from the beam weight and a hypergeometric function (HF) that represents the effect of outdated CSI on the transmission performance. However, it may require very high computational complexity to calculate the beam weight and the HF in m-MIMO environments. To alleviate the complexity problem, we determine the beam weight in dominant eigen-direction of CCM and approximate the HF as a function of temporal channel correlation. Since we may estimate the sum-rate by exploiting spatial and temporal channel correlation, we may need to update the resource allocation only when the change of CCM or temporal channel correlation is large enough to affect the sum-rate. Simulation results show that the proposed scheme provides performance similar to a greedy algorithm based on accurate sum-rate, while significantly reducing the computational complexity.기지국이 수많은 안테나를 활용하여 높은 전송 이득을 얻을 수 있는 대규모 다중 안테나(massive MIMO) 시스템이 차세대 무선 통신 시스템으로 각광받고 있다. 이를 위해서는 정확한 채널 정보(channel state information)를 기반으로 하는 신호 전송 및 자원 관리 기술이 필수적이다. 하지만 사용자가 고속으로 이동하는 환경에서는 기지국이 추정한 채널 정보와 실제 전송 채널이 크게 달라지는 채널 변화 효과(channel aging effect)가 발생하여, 시스템 전송 성능이 심각하게 하락할 수 있다. 위 문제를 해결하기 위하여, 상대적으로 사용자 이동성에 느리게 변화하는 공간 상관도 행렬(channel correlation matrix)을 활용할 수 있다. 하지만 대규모 다중 안테나 시스템에서는 기지국이 공간 상관도 행렬을 추정하는 과정에서 큰 파일럿(pilot) 신호 부담이 발생할 수 있다. 본 논문은 고속 이동 환경에서의 대규모 다중 안테나 시스템에서 다중 사용자에 대한 신호 전송을 고려한다. 우선, 낮은 파일럿 신호 부담을 갖는 채널 정보 추정 방법을 제안한다. 대규모 다중 안테나 시스템에서 채널 정보 추정은 큰 파일럿 신호 부담을 야기할 수 있다. 이때 공간 상관도 행렬을 활용한 파일럿 신호 설계를 통하여 채널 정보 추정으로 인한 신호 부담을 효과적으로 감소시킬 수 있다. 하지만 이를 위해서는 공간 상관도 행렬을 추정해야 하며, 이 과정에서 큰 신호 부담이 야기될 수 있다. 제안 기법은 기지국이 균일한 선형 안테나 배열(uniform linear array)을 가지고 있는 환경에서, 같은 거리의 안테나 쌍들의 채널 간 공간 상관도가 유사하다는 특징을 활용하여, 상기 안테나 쌍들의 채널 간 공간 상관도를 최소자승추정법(least-square estimation)을 활용하여 추정한다. 그리고 추정된 공간 상관도의 평균제곱오차(mean-square error)를 추정하여, 상기 평균제곱오차가 큰 공간 상관도를 0으로 치환하여 공간 상관도 행렬의 추정 정확도를 높인다. 또한 상기 추정한 공간 상관도 행렬을 활용하여 낮은 신호 부담으로 채널 정보를 추정할 수 있는 것을 보인다. 둘째로, 사용자 이동성에 의한 채널 변화에 강인한 신호 전송 방법을 제안한다. 사용자들이 서로 다른 속도로 이동하는 환경에서는 채널 변화에 의한 신호 전송 성능 저하 역시 사용자마다 다르게 나타날 수 있다. 위 문제를 해결하기 위하여, 각 사용자에 대한 채널 변화 효과를 개별적으로 고려하면서 평균 신호 대 누수간섭 및 잡음비(signal-to-leakage-plus-noise ratio)를 최대화하는 전송 빔 가중치를 설계한다. 제안 기법은 사용자들의 채널 정보와 공간 상관도 행렬의 선형 결합의 고유방향(eigen-direction)으로 신호를 전송한다. 또한 제안 기법을 사용할 때의 신호 대 간섭 및 잡음비(signal-to-interference-plus-noise ratio)를 분석하고, 이를 기반으로 하는 전송 전력 분배 방법을 제안한다. 끝으로, 사용자 이동성에 따른 채널 변화를 고려하는 자원 할당 방법을 제안한다. 이를 위하여, 상기 채널 변화를 고려하여 시스템 전송 성능(sum-rate)을 최대화하는 탐욕(greedy) 알고리듬 기반의 자원 할당 기술을 설계한다. 고속 이동 환경에서 시스템 전송 성능을 추정하기 위해서는 사용자들에 대한 전송 빔 가중치와 행렬에 대한 초기하 함수(hypergeometric function of a matrix argument)와 관련된 복잡한 연산이 필요하다. 이 문제를 해결하기 위하여, 빔 가중치를 공간 상관도 행렬의 고유방향으로 결정하고, 초기하 함수를 채널 시간 상관도에 대한 함수로 근사한다. 상기 전송 성능 추정 방법이 채널의 공간 및 시간 상관도에만 의존한다는 점을 활용하여, 채널 공간 및 시간 상관도가 크게 변화한 사용자가 존재할 때에 한하여 사용자들에 대한 자원 할당 상태를 갱신하는 방법을 제안한다. 실험을 통하여, 제안 기법이 복잡한 시스템 전송 성능을 기반으로 하는 자원 할당 방법과 유사한 자원 할당 성능을 보이면서도 계산 복잡도를 획기적으로 줄이는 것을 보인다.Abstract i Contents v List of Figures vii List of Tables ix Chapter 1. Introduction 1 Chapter 2. M-MIMO systems in the presence of channel aging effect 9 Chapter 3. Estimation of channel correlation matrix 13 3.1. Previous works 14 3.2. Proposed scheme 19 3.3. Performance evaluation 29 Chapter 4. Mobility-aware signal transmission in m-MIMO systems 43 4.1. Previous works 44 4.2. Proposed scheme 46 4.3. Performance evaluation 62 Chapter 5. Mobility-aware resource allocation in m-MIMO systems 73 5.1. Sum-rate-based greedy algorithm 74 5.2. Proposed scheme 76 5.3. Performance evaluation 88 Chapter 6. Conclusions 99 Appendix 103 References 105 Korean Abstract 115 Acknowledgement 119Docto

Técnicas de pré-codificação para sistemas multicelulares coordenados

Doutoramento em TelecomunicaçõesCoordenação Multicélula é um tópico de investigação em rápido crescimento e uma solução promissora para controlar a interferência entre células em sistemas celulares, melhorando a equidade do sistema e aumentando a sua capacidade. Esta tecnologia já está em estudo no LTEAdvanced sob o conceito de coordenação multiponto (COMP). Existem várias abordagens sobre coordenação multicélula, dependendo da quantidade e do tipo de informação partilhada pelas estações base, através da rede de suporte (backhaul network), e do local onde essa informação é processada, i.e., numa unidade de processamento central ou de uma forma distribuída em cada estação base. Nesta tese, são propostas técnicas de pré-codificação e alocação de potência considerando várias estratégias: centralizada, todo o processamento é feito na unidade de processamento central; semidistribuída, neste caso apenas parte do processamento é executado na unidade de processamento central, nomeadamente a potência alocada a cada utilizador servido por cada estação base; e distribuída em que o processamento é feito localmente em cada estação base. Os esquemas propostos são projectados em duas fases: primeiro são propostas soluções de pré-codificação para mitigar ou eliminar a interferência entre células, de seguida o sistema é melhorado através do desenvolvimento de vários esquemas de alocação de potência. São propostas três esquemas de alocação de potência centralizada condicionada a cada estação base e com diferentes relações entre desempenho e complexidade. São também derivados esquemas de alocação distribuídos, assumindo que um sistema multicelular pode ser visto como a sobreposição de vários sistemas com uma única célula. Com base neste conceito foi definido uma taxa de erro média virtual para cada um desses sistemas de célula única que compõem o sistema multicelular, permitindo assim projectar esquemas de alocação de potência completamente distribuídos. Todos os esquemas propostos foram avaliados em cenários realistas, bastante próximos dos considerados no LTE. Os resultados mostram que os esquemas propostos são eficientes a remover a interferência entre células e que o desempenho das técnicas de alocação de potência propostas é claramente superior ao caso de não alocação de potência. O desempenho dos sistemas completamente distribuídos é inferior aos baseados num processamento centralizado, mas em contrapartida podem ser usados em sistemas em que a rede de suporte não permita a troca de grandes quantidades de informação.Multicell coordination is a promising solution for cellular wireless systems to mitigate inter-cell interference, improving system fairness and increasing capacity and thus is already under study in LTE-A under the coordinated multipoint (CoMP) concept. There are several coordinated transmission approaches depending on the amount of information shared by the transmitters through the backhaul network and where the processing takes place i.e. in a central processing unit or in a distributed way on each base station. In this thesis, we propose joint precoding and power allocation techniques considering different strategies: Full-centralized, where all the processing takes place at the central unit; Semi-distributed, in this case only some process related with power allocation is done at the central unit; and Fulldistributed, where all the processing is done locally at each base station. The methods are designed in two phases: first the inter-cell interference is removed by applying a set of centralized or distributed precoding vectors; then the system is further optimized by centralized or distributed power allocation schemes. Three centralized power allocation algorithms with per-BS power constraint and different complexity tradeoffs are proposed. Also distributed power allocation schemes are proposed by considering the multicell system as superposition of single cell systems, where we define the average virtual bit error rate (BER) of interference-free single cell system, allowing us to compute the power allocation coefficients in a distributed manner at each BS. All proposed schemes are evaluated in realistic scenarios considering LTE specifications. The numerical evaluations show that the proposed schemes are efficient in removing inter-cell interference and improve system performance comparing to equal power allocation. Furthermore, fulldistributed schemes can be used when the amounts of information to be exchanged over the backhaul is restricted, although system performance is slightly degraded from semi-distributed and full-centralized schemes, but the complexity is considerably lower. Besides that for high degrees of freedom distributed schemes show similar behaviour to centralized ones

Esquemas de cooperação entre estações base para o LTE no sentido descendente

The explosive growth in wireless traffic and in the number of connected devices as smart phones or computers, are causing a dramatic increase in the levels of interference, which significantly degrades the capacity gains promised by the point-to-point multi input, multi output (MIMO) based techniques. Therefore, it is becoming increasingly clear that major new improvements in spectral efficiency of wireless networks will have to entail addressing intercell interference. So, there is a need for a new cellular architecture that can take these factors under consideration. It is in this context that LTE-Advanced arises. One of the most promising LTE-Advanced technology is Coordinated Multipoint (CoMP), which allows base stations to cooperate among them, in order to mitigate or eliminate the intercell interference and, by doing so, increase the system’s capacity. This thesis intends to study this concept, implementing some schemes that fall under the CoMP concept. In this thesis we consider a distributed precoded multicell approach, where the precoders are computed locally at each BS to mitigate the intercell interference. Two precoder are considered: distributed zero forcing (DZF) and distributed virtual signal-to-interference noise ratio (DVSINR) recently proposed. Then the system is further optimized by computing a power allocation algorithm over the subcarriers that minimizes the average bit error rate (BER). The considered algorithms are also evaluated under imperfect channel state information. A quantized version of the CSI associated to the different links between the BS and the UT is feedback from the UT to the BS. This information is then employed by the different BSs to perform the precoding design. A new DVSINR precoder explicitly designed under imperfect CSI is proposed. The proposed schemes were implemented considering the LTE specifications, and the results show that the considered precoders are efficiently to remove the interference even under imperfect CSI.O crescimento exponencial no tráfego de comunicações sem-fios e no número de dispositivos utilizados (smart phones, computadores portáteis, etc.) está a causar um aumento significativo nos níveis de interferência, que prejudicam significativamente os ganhos de capacidade assegurados pelas tecnologias baseadas em ligações ponto-a-ponto MIMO. Deste modo, torna-se cada vez mais necessário que os grandes aperfeiçoamentos na eficiência espectral de sistemas de comunicações sem-fios tenham em consideração a interferência entre células. De forma a tomar em consideração estes aspectos, uma nova arquitectura celular terá de ser desenvolvida. É assim, neste contexto, que surge o LTE-Advanced. Uma das tecnologias mais promissoras do LTE-Advanced é a Coordenação Multi-Ponto (CoMP), que permite que as estações base cooperem de modo a mitigar a interferência entre células e, deste modo, aumentar a capacidade do sistema. Esta dissertação pretende estudar este conceito, implementando para isso algumas técnicas que se enquadram no conceito do CoMP. Nesta dissertação iremos considerar a implementação de um sistema de pré-codificação em múltiplas células, em que os pré-codificadores são calculados em cada BS, de modo a mitigar a interferência entre células. São considerados dois pré-codificadores: Distributed Zero Forcing (DZF) e Distributed Virtual Signal-to-Interferance Noise Ratio (DVSINR), recentemente proposto. De seguida o sistema é optimizado com a introdução de algoritmos de alocação de potência entre as sub-portadoras com o objectivo de minimizar a taxa média de erros (BER). Os algoritmos considerados são também avaliados em situações em que a informação do estado do canal é imperfeita. Uma versão quantizada da CSI associada a cada uma das diferentes ligações entre as BS e os UT é assim enviada do UT para a BS. Esta informação é então utilizada para calcular os diferentes pré-codificadores em cada BS. Uma nova versão do pré-codificador DVSINR é proposta de modo a lidar com CSI imperfeito. Os esquemas propostos foram implementados considerandos especificações do LTE, e os resultados obtidos demonstram que os pré-codificadores removem de uma forma eficiente a interferência, mesmo em situações em que a CSI é imperfeita

Radio Resource Management for New Application Scenarios in 5G: Optimization and Deep Learning

The fifth-generation (5G) New Radio (NR) systems are expected to support a wide range of emerging applications with diverse Quality-of-Service (QoS) requirements. New application scenarios in 5G NR include enhanced mobile broadband (eMBB), massive machine-type communication (mMTC), and ultra-reliable low-latency communications (URLLC). New wireless architectures, such as full-dimension (FD) massive multiple-input multiple-output (MIMO) and mobile edge computing (MEC) system, and new coding scheme, such as short block-length channel coding, are envisioned as enablers of QoS requirements for 5G NR applications. Resource management in these new wireless architectures is crucial in guaranteeing the QoS requirements of 5G NR systems. The traditional optimization problems, such as subcarriers and user association, are usually non-convex or Non-deterministic Polynomial-time (NP)-hard. It is time-consuming and computing-expensive to find the optimal solution, especially in a large-scale network. To solve these problems, one approach is to design a low-complexity algorithm with near optimal performance. In some cases, the low complexity algorithms are hard to obtain, deep learning can be used as an accurate approximator that maps environment parameters, such as the channel state information and traffic state, to the optimal solutions. In this thesis, we design low-complexity optimization algorithms, and deep learning frameworks in different architectures of 5G NR to resolve optimization problems subject to QoS requirements. First, we propose a low-complexity algorithm for a joint cooperative beamforming and user association problem for eMBB in 5G NR to maximize the network capacity. Next, we propose a deep learning (DL) framework to optimize user association, resource allocation, and offloading probabilities for delay-tolerant services and URLLC in 5G NR. Finally, we address the issue of time-varying traffic and network conditions on resource management in 5G NR

D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies

This document provides the most recent updates on the technical contributions and research challenges focused in WP3. Each Technology Component (TeC) has been evaluated under possible uniform assessment framework of WP3 which is based on the simulation guidelines of WP6. The performance assessment is supported by the simulation results which are in their mature and stable state. An update on the Most Promising Technology Approaches (MPTAs) and their associated TeCs is the main focus of this document. Based on the input of all the TeCs in WP3, a consolidated view of WP3 on the role of multinode/multi-antenna transmission technologies in 5G systems has also been provided. This consolidated view is further supported in this document by the presentation of the impact of MPTAs on METIS scenarios and the addressed METIS goals.Aziz, D.; Baracca, P.; De Carvalho, E.; Fantini, R.; Rajatheva, N.; Popovski, P.; Sørensen, JH.... (2015). D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies. http://hdl.handle.net/10251/7675

Resource Allocation for Coordinated Multipoint Joint Transmission System and Received Signal Strength Based Positioning in Long Term Evolution Network

The Long-Term Evolution Advanced (LTE-A) system are expected to provide high speed and high quality services, which are supported by emerging technologies such as Coordinated Multipoint (CoMP) transmission and reception. Dynamic resource allocation plays a vital role in LTE-A design and planning, which is investigated in this thesis. In addition, Received Signal Strength (RSS) based positioning is also investigated in orthogonal frequency division multiplexing (OFDM) based wireless networks, which is based on an industry project. In the first contribution, a physical resource blocks (PRB) allocation scheme with fuzzy logic based user selection is proposed. This work considers three parameters and exploit a fuzzy logic (FL) based criterion to categorize users. As a result, it enhances accuracy of user classification. This work improves system capacity by a ranking based PRBs allocation schemes. Simulation results show that proposed fuzzy logic based user selection scheme improves performance for CoMP users. Proposed ranking based greedy allocation algorithm cut complexity in half but maintain same performance. In the second contribution, a two-layer proportional-fair (PF) user scheduling scheme is proposed. This work focused on fairness between CoMP and Non-CoMP users instead of balancing fairness in each user categories. Proposed scheme jointly optimizes fairness and system capacity over both CoMP and Non-CoMP users. Simulation results show that proposed algorithm significantly improves fairness between CoMP and Non-CoMP users. In the last contribution, RSS measurement method in LTE system is analyzed and a realizable RSS measurement method is proposed to fight against multipath effect. Simulation results shows that proposed method significantly reduced measurement error caused by multipath. In RSS based positioning area, this is the first work that consider exploiting LTE’s own signal strength measurement mechanism to enhance accuracy of positioning. Furthermore, the proposed method can be deployed in modern LTE system with limited cost

Intelligent and Efficient Ultra-Dense Heterogeneous Networks for 5G and Beyond

Ultra-dense heterogeneous network (HetNet), in which densified small cells overlaying the conventional macro-cells, is a promising technique for the fifth-generation (5G) mobile network. The dense and multi-tier network architecture is able to support the extensive data traffic and diverse quality of service (QoS) but meanwhile arises several challenges especially on the interference coordination and resource management. In this thesis, three novel network schemes are proposed to achieve intelligent and efficient operation based on the deep learning-enabled network awareness. Both optimization and deep learning methods are developed to achieve intelligent and efficient resource allocation in these proposed network schemes. To improve the cost and energy efficiency of ultra-dense HetNets, a hotspot prediction based virtual small cell (VSC) network is proposed. A VSC is formed only when the traffic volume and user density are extremely high. We leverage the feature extraction capabilities of deep learning techniques and exploit a long-short term memory (LSTM) neural network to predict potential hotspots and form VSC. Large-scale antenna array enabled hybrid beamforming is also adaptively adjusted for highly directional transmission to cover these VSCs. Within each VSC, one user equipment (UE) is selected as a cell head (CH), which collects the intra-cell traffic using the unlicensed band and relays the aggregated traffic to the macro-cell base station (MBS) in the licensed band. The inter-cell interference can thus be reduced, and the spectrum efficiency can be improved. Numerical results show that proposed VSCs can reduce $55\%$ power consumption in comparison with traditional small cells. In addition to the smart VSCs deployment, a novel multi-dimensional intelligent multiple access (MD-IMA) scheme is also proposed to achieve stringent and diverse QoS of emerging 5G applications with disparate resource constraints. Multiple access (MA) schemes in multi-dimensional resources are adaptively scheduled to accommodate dynamic QoS requirements and network states. The MD-IMA learns the integrated-quality-of-system-experience (I-QoSE) by monitoring and predicting QoS through the LSTM neural network. The resource allocation in the MD-IMA scheme is formulated as an optimization problem to maximize the I-QoSE as well as minimize the non-orthogonality (NO) in view of implementation constraints. In order to solve this problem, both model-based optimization algorithms and model-free deep reinforcement learning (DRL) approaches are utilized. Simulation results demonstrate that the achievable I-QoSE gain of MD-IMA over traditional MA is $15\%$ - $18\%$. In the final part of the thesis, a Software-Defined Networking (SDN) enabled 5G-vehicle ad hoc networks (VANET) is designed to support the growing vehicle-generated data traffic. In this integrated architecture, to reduce the signaling overhead, vehicles are clustered under the coordination of SDN and one vehicle in each cluster is selected as a gateway to aggregate intra-cluster traffic. To ensure the capacity of the trunk-link between the gateway and macro base station, a Non-orthogonal Multiplexed Modulation (NOMM) scheme is proposed to split aggregated data stream into multi-layers and use sparse spreading code to partially superpose the modulated symbols on several resource blocks. The simulation results show that the energy efficiency performance of proposed NOMM is around 1.5-2 times than that of the typical orthogonal transmission scheme

Channel Prediction for Mobile MIMO Wireless Communication Systems

Temporal variation and frequency selectivity of wireless channels constitute a major drawback to the attainment of high gains in capacity and reliability offered by multiple antennas at the transmitter and receiver of a mobile communication system. Limited feedback and adaptive transmission schemes such as adaptive modulation and coding, antenna selection, power allocation and scheduling have the potential to provide the platform of attaining the high transmission rate, capacity and QoS requirements in current and future wireless communication systems. Theses schemes require both the transmitter and receiver to have accurate knowledge of Channel State Information (CSI). In Time Division Duplex (TDD) systems, CSI at the transmitter can be obtained using channel reciprocity. In Frequency Division Duplex (FDD) systems, however, CSI is typically estimated at the receiver and fed back to the transmitter via a low-rate feedback link. Due to the inherent time delays in estimation, processing and feedback, the CSI obtained from the receiver may become outdated before its actual usage at the transmitter. This results in significant performance loss, especially in high mobility environments. There is therefore a need to extrapolate the varying channel into the future, far enough to account for the delay and mitigate the performance degradation. The research in this thesis investigates parametric modeling and prediction of mobile MIMO channels for both narrowband and wideband systems. The focus is on schemes that utilize the additional spatial information offered by multiple sampling of the wave-field in multi-antenna systems to aid channel prediction. The research has led to the development of several algorithms which can be used for long range extrapolation of time-varyingchannels. Based on spatial channel modeling approaches, simple and efficient methods for the extrapolation of narrowband MIMO channels are proposed. Various extensions were also developed. These include methods for wideband channels, transmission using polarized antenna arrays, and mobile-to-mobile systems. Performance bounds on the estimation and prediction error are vital when evaluating channel estimation and prediction schemes. For this purpose, analytical expressions for bound on the estimation and prediction of polarized and non-polarized MIMO channels are derived. Using the vector formulation of the Cramer Rao bound for function of parameters, readily interpretable closed-form expressions for the prediction error bounds were found for cases with Uniform Linear Array (ULA) and Uniform Planar Array (UPA). The derived performance bounds are very simple and so provide insight into system design. The performance of the proposed algorithms was evaluated using standardized channel models. The effects of the temporal variation of multipath parameters on prediction is studied and methods for jointly tracking the channel parameters are developed. The algorithms presented can be utilized to enhance the performance of limited feedback and adaptive MIMO transmission schemes

Security and Privacy for Modern Wireless Communication Systems

The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks