Channel Knowledge Acquisition in Relay and Multipoint-to-Multipoint Transmission Systems

Minn, Hlaing; Muñoz, Daniel

doi:10.1109/tvt.2014.2330992

Cited by 7 publications

(1 citation statement)

References 33 publications

(48 reference statements)

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“…All system nodes are equipped with multiple antennas, where N A , N B , N E , and N W denote the number of antennas at Alice, Bob, Wiley, and Eve, respectively. We assume that Bob and Eve can perfectly estimate their individual CSI, while Alice knows Bob's channel perfectly (we assume there is a separate and reliable mechanism to accurately acquire the CSI, for instance, by assuming channel reciprocity in time-division duplex (TDD) systems or by using dedicated pilot sequences [37]) but has just a statistical knowledge of Eve's CSI. Additionally, Bob and Alice share an open errorfree feedback channel, which Bob utilizes to send back the index of Alice's antenna that allows achieving the best SNR at Bob, along with its corresponding value to enable ON-OFF transmissions, i.e., Alice transmits only when Bob's SNR exceeds some SNR threshold μ. Alice utilizes the index sent by Bob to implement TAS.…”

Section: System Modelmentioning

confidence: 99%

Secure Rate Control and Statistical QoS Provisioning for Cloud-Based IoT Networks

Irfan

Alves

López

2021

Security and Communication Networks

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The Internet of Things (IoT) facilitates physical things to detect, interact, and execute activities on-demand, enabling a variety of applications such as smart homes and smart cities. However, it also creates many potential risks related to data security and privacy vulnerabilities on the physical layer of cloud-based Internet of Things (IoT) networks. These can include different types of physical attacks such as interference, eavesdropping, and jamming. As a result, quality-of-service (QoS) provisioning gets difficult for cloud-based IoT. This paper investigates the statistical QoS provisioning of a four-node cloud-based IoT network under security, reliability, and latency constraints by relying on the effective capacity model to offer enhanced QoS for IoT networks. Alice and Bob are legitimate nodes trying to communicate with secrecy in the considered scenario, while an eavesdropper Eve overhears their communication. Meanwhile, a friendly jammer, which emits artificial noise, is used to degrade the wiretap channel. By taking advantage of their multiple antennas, Alice implements transmit antenna selection, while Bob and Eve perform maximum-ratio combining. We further assume that Bob decodes the artificial noise perfectly and thus removes its contribution by implementing perfect successive interference cancellation. A closed-form expression for an alternative formulation of the outage probability, conditioned upon the successful transmission of a message, is obtained by considering adaptive rate allocation in an ON-OFF transmission. The data arriving at Alice’s buffer are modeled by considering four different Markov sources to describe different IoT traffic patterns. Then, the problem of secure throughput maximization is addressed through particle swarm optimization by considering the security, latency, and reliability constraints. Our results evidence the considerable improvements on the delay violation probability by increasing the number of antennas at Bob under strict buffer constraints.

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Section: System Modelmentioning

confidence: 99%

Secure Rate Control and Statistical QoS Provisioning for Cloud-Based IoT Networks

Irfan

Alves

López

2021

Security and Communication Networks

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Optimal precoders and power splitting factors in multiuser multiple‐input multiple‐output cognitive decode‐and‐forward relay systems with wireless energy harvesting

Kha

2021

Int J Communication

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This paper considers an underlay cognitive radio (CR) wireless network with the assistance of a two-hop decode-and-forward (DF) relay node. Different from the conventional CR relay networks, in this paper, the relay node using power-splitting (PS) techniques harvests wireless energy transmitted from the secondary base station (SBS) and, then, uses its harvested energy to forward the received signals to multiple secondary receive users (SRUs). Due to the highly mutual dependence of the transmission strategies at nodes on the system performance, the optimal design of signal processing at transceivers to efficiently handle the interference and energy constraints is crucial. This paper studies the jointly optimal design of the precoders, PS factors to maximize the minimum user rate under the transmit power, harvested energy, and interference power constraints. Owing to the nonlinearly and mutually coupled design matrix variables in both objective function and constraints, the joint design of the precoders and PS factors for the concerned problem is mathematically challenging. To tackle these difficulties, we devise the appropriate surrogate functions to recast the nonconvex optimization problem into the convex one.By using the minorization-maximization framework, an efficient iterative algorithm with provable convergence is developed by solving the convex optimization problem in each iteration. Numerical results are provided to evaluate the achievable user rate performance of the considered system and investigate the effects of the interference power thresholds at the primary receive users and the number of antennas at the SBS and the relay on the minimum achievable user rate. K E Y W O R D S cognitive radio, MIMO users, relay networks, simultaneously wireless information and power transfer (SWIPT) 1 | INTRODUCTION Cognitive radio (CR) has been recognized as an effective means to deal with the spectrum scarcity for the next generation of wireless communications. In underlay CR approaches, secondary users (SUs) can communicate at the same time

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Inter-Relay Interference Cancellation Using MIMO Detection

Lee

Kim

Song

2017

Wireless Pers Commun

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Channel Knowledge Acquisition in Relay and Multipoint-to-Multipoint Transmission Systems

Cited by 7 publications

References 33 publications

Secure Rate Control and Statistical QoS Provisioning for Cloud-Based IoT Networks

Secure Rate Control and Statistical QoS Provisioning for Cloud-Based IoT Networks

Optimal precoders and power splitting factors in multiuser multiple‐input multiple‐output cognitive decode‐and‐forward relay systems with wireless energy harvesting

Inter-Relay Interference Cancellation Using MIMO Detection

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