03425nam a22003854u 450000100220000000300060002200500170002800700150004500800410006002000300010102400310013104100080016210000180017024500940018825000060028226000160028826400160030430000120032033600260033233700260035833800360038434700210042034700080044152019250044965000370237465000220241165000290243365302330246270000240269570000180271970000220273777600360275985601020279585601420289710.1002/9781394183111Wiley20251030120313.0cr nn 008mam|a241030t2024||||xxu    fs|   |0|| 0|eng||  a9781394183111qelectronic7 a10.1002/97813941831112doi  aeng1 aHan, Rui4aut10aIoT Signal Detectionh[electronic resource]cRui Han, Jingjing Wang, Lin Bai, Jianwei Liu  a1  bWileyc2024 1bWileyc2024  a208pp.;  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext file2rdaft  bPDF  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. 4aMobile & Wireless Communications 4aSignal Processing 4aCommunication Technology00aInternet 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 sensing1 aWang, Jingjing4aut1 aBai, Lin4aut1 aLiu, Jianwei4aut08iPrinted edition:z978139418308140uhttps://onlinelibrary.wiley.com/action/showBook?doi=10.1002%2F9781394183111aWiley Online Library423Cover Imageuhttps://onlinelibrary.wiley.com/cms/asset/0b3449a8-66c0-4091-a3ab-05c8e37228d8/9781394183111.cover.gifaWiley Online Library