000			03528nam a22004094u 4500
001			10.1002/9781394183111
003			Wiley
005			20251030120313.0
007			cr nn 008mam|a
008			241030t2024||||xxu fs| |0|| 0|eng||
020			_a9781394183111 _qelectronic
024	7		_a10.1002/9781394183111 _2doi
041			_aeng
100	1		_aHan, Rui _4aut _991871
245	1	0	_aIoT Signal Detection _h[electronic resource] _cRui Han, Jingjing Wang, Lin Bai, Jianwei Liu
250			_a1
260			_bWiley _c2024
264		1	_bWiley _c2024
300			_a208pp.;
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _2rdaft
347			_bPDF
520			_aComprehensive reference covering signal detection for random access in IoT systems from the beginner to expert level With a carefully balanced blend of theoretical elements and applications, IoT Signal Detection is an easy-to-follow presentation on signal detection for IoT in terms of device activity detection, sparse signal detection, collided signal detection, round-trip delay estimation, and backscatter signal division, building progressively from basic concepts and important background material up to an advanced understanding of the subject. Various signal detection and estimation techniques are explained, e.g., variational inference algorithm and compressive sensing reconstruction algorithm, and a number of recent research outcomes are included to provide a review of the state of the art in the field. Written by four highly qualified academics, IoT Signal Detection discusses sample topics such as: ML, ZF, and MMSE detection, Markov chain Monte Carlo-based detection, variational inference-based detection, compressive sensing-based detection Sparse signal detection for multiple access, covering Bayesian compressive sensing algorithm and structured subspace pursuit algorithm Collided signal detection for multiple access using automatic modulation classification algorithm, round-trip delay estimation for collided signals Signal detection for backscatter signals, covering central limited theorem-based detection including detection algorithms, performance analysis, and simulation results Signal design for multi-cluster coordination, covering successive interference cancellation design, device grouping and power control, and constructive interference-aided multi-cluster coordination With seamless coverage of the subject presented in a linear and easy-to-understand way, IoT Signal Detection is an ideal reference for both graduate students and practicing engineers in wireless communications.
650		4	_aMobile & Wireless Communications
650		4	_aSignal Processing
650		4	_aCommunication Technology
653	0	0	_aInternet of Things; signal detection; random access; non-orthogonal random access; grant-free random access; signal collision; sparse signal; round-trip delay; Markov chain Monte Carlo; variational inference; compressive sensing
700	1		_aWang, Jingjing _4aut _983630
700	1		_aBai, Lin _4aut _991872
700	1		_aLiu, Jianwei _4aut _991873
776	0	8	_iPrinted edition: _z9781394183081
856	4	0	_uhttps://onlinelibrary.wiley.com/action/showBook?doi=10.1002%2F9781394183111 _aWiley Online Library
856	4	2	_3Cover Image _uhttps://onlinelibrary.wiley.com/cms/asset/0b3449a8-66c0-4091-a3ab-05c8e37228d8/9781394183111.cover.gif _aWiley Online Library
999			_c67126 _d67126