A Unified Design of Massive Access for Cellular Internet of Things

et al. 2021

IEEE Trans. Commun.

We investigate massive access in the Internet-of-Things (IoT) relying on multi-pair two-way amplify-and-forward (AF) relay systems using massive multiple-input multiple-output (MIMO). We utilize the approximate message passing (AMP) algorithm for joint device activity detection and channel estimation. Furthermore, we analyze the achievable rates for multiple pairs of active devices and derive the closed-form expressions for both maximum-ratio combining/maximum-ratio transmission (MRC/MRT) and zero-forcing reception/zero-forcing transmission (ZFR/ZFT)-based beamforming schemes adopted at the relay. Moreover, to improve the achievable sum rates, we propose a low-complexity algorithm for optimizing the pilot length L. Our simulation results verify the accuracy of the closed-form expressions of the MRC/MRT and ZFR/ZFT scenarios. Finally, the proposed pilot-length optimization algorithm performs well in both the MRC/MRT and ZFR/ZFT scenarios.

“…Then the channel estimation error is given by e k = g k −ĝ k . Moreover, as M becomes large, the covariance matrices ofĝ k and e k can be respectively formulated as [8], [15]…”

Section: A Device Activity Detection and Channel Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis and Optimization of Massive Access to the IoT Relying on Multi-Pair Two-Way Massive MIMO Relay Systems

Peng

et al. 2021

IEEE Trans. Commun.

“…From (17) and (26), the estimation performance depends, to a great extent, on the cooperation strategy specified by the combiner c t lb . Similar to work [34], this paper adopts the following adaptive combiner…”

Section: Derivation Of Algorithm Recursionsmentioning

confidence: 99%

Cooperative Activity Detection: Sourced and Unsourced Massive Random Access Paradigms

Shao

IEEE Trans. Signal Process.

et al. 2020

Self Cite

This paper investigates the issue of cooperative activity detection for grant-free random access in the sixthgeneration (6G) cell-free wireless networks with sourced and unsourced paradigms. First, we propose a cooperative framework for solving the problem of device activity detection in sourced random access. In particular, multiple access points (APs) cooperatively detect the device activity via exchanging low-dimensional intermediate information with their neighbors. This is enabled by the proposed covariance-based algorithm via exploiting both the sparsity-promoting and similarity-promoting terms of the device state vectors among neighboring APs. A decentralized approximate separating approach is introduced based on the forward-backward splitting strategy for addressing the formulated problem. Then, the proposed activity detection algorithm is adopted as a decoder of cooperative unsourced random access, where the multiple APs cooperatively detect the list of transmitted messages regardless of the identity of the transmitting devices. Finally, we provide sufficient conditions on the step sizes that ensure the convergence of the proposed algorithm in the sense of Bregman divergence. Simulation results show that the proposed algorithm is efficient for addressing both sourced and unsourced massive random access problems, while requires a shorter signature sequence and accommodates a significantly larger number of active devices with a reasonable antenna array size, compared with the state-of-art algorithms.

“…However, the conventional multiple access protocols, e.g., ALOHA, which limit the number of access devices and require a high signalling overhead, are no longer really fit for the massive access systems [44,45]. To solve this problem, the grant-free random access protocol is widely applied in the massive access systems [46,47]. Specifically, each device is assigned with a unique pilot sequence for activity detection and channel estimation.…”

Section: Massive Access In Cellular Iotmentioning

confidence: 99%

Physical layer security for massive access in cellular Internet of Things

Zhong

et al. 2020

Sci. China Inf. Sci.

Self Cite

The upcoming fifth generation (5G) cellular network is required to provide seamless access for a massive number of Internet of Things (IoT) devices over the limited radio spectrum. In the context of massive spectrum sharing among heterogeneous IoT devices, wireless security becomes a critical issue owing to the broadcast nature of wireless channels. According to the characteristics of the cellular IoT network, physical layer security (PHY-security) is a feasible and effective way of realizing secure massive access. This article reviews the security issues in the cellular IoT network with an emphasis on revealing the corresponding challenges and opportunities for the design of secure massive access. Furthermore, we provide a survey on PHY-security techniques to improve the secrecy performance. Especially, we propose a secure massive access framework for the cellular IoT network by exploiting the inherent co-channel interferences. Finally, we discuss several potential research directions to further enhance the security of massive IoT.