Game-Theoretic Beamforming and Power Allocation in MIMO Cognitive Radio Systems with Transmitter Antenna Correlation

Detection of Alzheimer's disease and mild cognitive impairment based on structural volumetric MR images using 3D-DWT and WTA-KSVM trained by PSOTVAC

Opportunistic unlicensed access to the (tem- porarily) unused frequency bands across the licensed radio spectrum is currently being inves- tigated as a means to increase the efficiency of spectrum usage. Such opportunistic access calls for implementation of safeguards so that ongo- ing licensed operations are not compromised. Among different candidates, sensing-based access, where the unlicensed users transmit if they sense the licensed band to be free, is partic- ularly appealing due to its low deployment cost and its compatibility with the legacy licensed sys- tems. The ability to reliably and autonomously identify unused frequency bands is envisaged as one of the main functionalities of cognitive radios. In this article we provide an overview of the regulatory requirements and major chal- lenges associated with the practical implementa- tion of spectrum sensing functionality in cognitive radio systems. Furthermore, we outline different design trade-offs that have to be made in order to enhance various aspects of the sys- tem’s performance.

作者：Professor Kwang-Cheng Chen，Professor Ramjee Prasad 出版：Wiley 2009 目录 Preface xi 1 Wireless Communications 1 1.1 Wireless Communications Systems 1 1.2 Orthogonal Frequency Division Multiplexing (OFDM) 3 1.2.1 OFDM Concepts 4 1.2.2 Mathematical Model of OFDM System 5 1.2.3 OFDM Design Issues 9 1.2.4 OFDMA 21 1.3 MIMO 24 1.3.1 Space-Time Codes 24 1.3.2 Spatial Multiplexing Using Adaptive Multiple Antenna Techniques 27 1.3.3 Open-loop MIMO Solutions 27 1.3.4 Closed-loop MIMO Solutions 29 1.3.5 MIMO Receiver Structure 31 1.4 Multi-user Detection (MUD) 34 1.4.1 Multi-user (CDMA) Receiver 34 1.4.2 Suboptimum DS/CDMA Receivers 37 References 40 2 Software Defined Radio 41 2.1 Software Defined Radio Architecture 41 2.2 Digital Signal Processor and SDR Baseband Architecture 43 2.3 Reconfigurable Wireless Communication Systems 46 2.3.1 Unified Communication Algorithm 46 2.3.2 Reconfigurable OFDM Implementation 47 2.3.3 Reconfigurable OFDM and CDMA 47 2.4 Digital Radio Processing 48 2.4.1 Conventional RF 48 2.4.2 Digital Radio Processing (DRP) Based System Architecture 52 References 58 3 Wireless Networks 59 3.1 Multiple Access Communications and ALOHA 60 3.1.1 ALOHA Systems and Slotted Multiple Access 61 3.1.2 Slotted ALOHA 61 3.1.3 Stabilised Slotted ALOHA 64 3.1.4 Approximate Delay Analysis 65 3.1.5 Unslotted ALOHA 66 3.2 Splitting Algorithms 66 3.2.1 Tree Algorithms 67 3.2.2 FCFS Splitting Algorithm 68 3.2.3 Analysis of FCFS Splitting Algorithm 69 3.3 Carrier Sensing 71 3.3.1 CSMA Slotted ALOHA 71 3.3.2 Slotted CSMA 76 3.3.3 Carrier Sense Multiple Access with Collision Detection (CSMA/CD) 79 3.4 Routing 82 3.4.1 Flooding and Broadcasting 83 3.4.2 Shortest Path Routing 83 3.4.3 Optimal Routing 83 3.4.4 Hot Potato (Reflection) Routing 84 3.4.5 Cut-through Routing 84 3.4.6 Interconnected Network Routing 84 3.4.7 Shortest Path Routing Algorithms 84 3.5 Flow Control 89 3.5.1 Window Flow Control 89 3.5.2 Rate Control Schemes 91 3.5.3 Queuing Analysis of the Leaky Bucket Scheme 9

ABSTRACT With the development of network-enabled sensors and articial intelligence algorithms, various human-centered smart systems are proposed to provide services with higher quality, such as smart healthcare, affective interaction, and autonomous driving. Considering cognitive computing is an indispensable technology to develop these smart systems, this paper proposes human-centered computing assisted by cognitive computing and cloud computing. First, we provide a comprehensive investigation of cognitive computing, including its evolution from knowledge discovery, cognitive science, and big data. Then, the system architecture of cognitive computing is proposed, which consists of three critical technologies, i.e., networking (e.g., Internet of Things), analytics (e.g., reinforcement learning and deep learning), and cloud computing. Finally, it describes the representative applications of human-centered cognitive computing, including robot technology, emotional communication system, and medical cognitive system.

神经形态认知

压缩感知的基础阶论文，对初学者应该很有用处，共有两篇综述论文和一个ppt。