Identification of active users for grant-free massive connectivity in large scale antenna systems |
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| Institution: | 1. Maulana Abul Kalam Azad University of Technology, Nadia 741249, West Bengal, India;2. National Institute of Technology, Durgapur 713209, India;3. National Institute of Technical Teachers’ Training and Research, Kolkata 700106, India;4. Yuzuncu Yil University, Van 65080, Turkey;5. School of Computer Science & Engineering, XIM University, Bhubaneswar 751013, India;6. Global Institute of Science and Technology, Haldia 721657, West Bengal, India;1. School of Electronics Engineering, Kyungpook National University, 80 Daehakro, Bukgu, Daegu 41566, Republic of Korea;2. Department of Control and Instrumentation Engineering, Pukyong National University, 45 Yongsoro, Namgu, Busan 48513, Republic of Korea;1. School of Computer and Information Engineering, Fuyang Normal University, Fuyang 236037, China;2. College of Electronic and Optical Engineering & College of Microelectronics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China;3. College of Telecommunication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China;1. Department of Mathematics, Cochin University of Science and Technology, Kerala, India;2. Department of Mathematics, Gandhigram Rural Institute, Dindigul, Tamilnadu, India;1. Department of Mathematics, Hanoi Pedagogical University 2, Vinh Phuc, Viet Nam;2. ICRTM, Institute of Mathematics, VAST, 18 Hoang Quoc Viet Road, Hanoi, Viet Nam |
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| Abstract: | Conventional grant-based random access scheme is inappropriate to massive Internet of Things (IoT) connectivity since massive devices results in large number of collisions. This is unacceptable for the low latency requirement in 5 G and future networks. It is also not possible to assign orthogonal pilot sequences to all users to perform user activity detection (UAD) due to the massive number of devices and limited channel coherence time. In this paper, a novel grant-free (GF) UAD scheme is proposed with extremely low complexity and latency in an IoT network with a massive number of users. We exploit multiple antennas at the base station (BS) to produce spatial filtering by a fixed beamforming network (FBN), there then the inter-beam interference can be mitigated. Moreover, intra-beam interference is removed in temporal domain by orthogonal multiple access (OMA) technology. Joint UAD and multiuser detection (MUD) is realized by a bank of spatial-temporal matched filters at BS. The proposed method is efficient and the complexity is much less than the existing compressed sensing (CS)-based GF non-orthogonal multiple access (GFNOMA) algorithms. Performances of the proposed method is extensively analyzed in terms of the successful activity detection rate (SADR) as well as the Receiver operating characteristic (ROC) based on Neyman-Pearson (NP) decision rule. Numerical results demonstrate that it is comparable to the recently proposed iterative Maximum Likelihood (ML) algorithm, yet the computation load of the proposed scheme is extensively reduced. |
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