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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: closed (20 March 2024) | Viewed by 3869

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Dr. Raveendra K. Rao

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Guest Editor

Department of Electrical and Computer Engineering, Western University, London, ON N6A5B9, Canada
Interests: communication systems and data networking; digital modulations; wireless digital communications; satellite communications; distributed detection; OFDM dystems

Special Issue Information

Dear Colleagues,

Given the incessant escalation of wireless tele-traffic, the impending spectrum crunch can only be circumvented by the migration to millimetre-wave (mmWave) carriers. However, since radar sensing technologies also rely on mmWave carriers, the bandwidth of sensing and wireless communications might begin to overlap. However, it is possible to economize these carriers using sophisticated bandwidth sharing in next-generation wireless communications (6G) with the aid of integrated sensing and communication (ISAC). The ultimate goal of ISAC is to integrate and unify communication and radio sensing operations toward a mutually beneficial relationship. The benefits of ISAC can be divided into two categories: 1) integration gain to use spectrum resources efficiently, and 2) coordination gain to balance the mutual functions. It is expected that ISAC will have broad prospective applications as the foundation of future 6G wireless networks. This Special Issue aims to attract novel and solid contributions to ISAC. Contributions are solicited on, but not necessarily limited to, the following topics:

Fundamental limits and performance analysis of ISAC;
Advanced waveform, channel coding, and modulation designs for ISAC;
Novel multiple access designs for ISAC;
Machine learning aided ISAC;
MIMO/Massive-MIMO-assisted ISAC;
ISAC for emerging physical-layer technologies;
Implementation of ISAC in 6G applications, e.g., SAGINs, VR, AR.

Dr. Raveendra K. Rao
Guest Editor

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Published Papers (4 papers)

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Research

22 pages, 1183 KiB

Open AccessArticle

Multistatic Integrated Sensing and Communication System Based on Macro–Micro Cooperation

by Xiaoyun Wang, Zixiang Han, Jing Jin, Rongyan Xi, Yajuan Wang, Lincong Han, Liang Ma, Mengting Lou, Xin Gui, Qixing Wang and Guangyi Liu

Sensors 2024, 24(8), 2498; https://doi.org/10.3390/s24082498 - 13 Apr 2024

Viewed by 563

Abstract

A novel multistatic integrated sensing and communication (ISAC) system based on macro–micro cooperation for the sixth-generation (6G) mobile network is proposed. Instead of using macrosites at both the transmitter and receiver sides, microsites are considered as receivers in cooperative sensing. This system is important since microsites can be deployed more flexibly to reduce their distances to the sensing objects, providing better coverage for sensing service. In this work, we first analyze the deployment problem of microsites, which can be deployed along the radius and azimuth angle to cover macrosite cells. The coverage area of each microsite is derived in terms of its position in the cell. Then, we describe an efficient estimating approach for obtaining the position and velocity of sensing objects in the macrosite cell. By choosing multiple microsites around the targeted sensing area, joint data processing with an efficient optimization method is also provided. Simulation results show that the multistatic ISAC system employing macro–micro cooperation can improve the position and velocity estimation accuracy of objects compared to systems employing macrosite cooperation alone, demonstrating the effectiveness and potential for implementing the proposed system in the 6G mobile network. Full article

(This article belongs to the Special Issue Integrated Sensing and Communication)

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17 pages, 494 KiB

Open AccessArticle

Robust Offloading for Edge Computing-Assisted Sensing and Communication Systems: A Deep Reinforcement Learning Approach

by Li Shen, Bin Li and Xiaojie Zhu

Sensors 2024, 24(8), 2489; https://doi.org/10.3390/s24082489 - 12 Apr 2024

Viewed by 333

Abstract

In this paper, we consider an integrated sensing, communication, and computation (ISCC) system to alleviate the spectrum congestion and computation burden problem. Specifically, while serving communication users, a base station (BS) actively engages in sensing targets and collaborates seamlessly with the edge server to concurrently process the acquired sensing data for efficient target recognition. A significant challenge in edge computing systems arises from the inherent uncertainty in computations, mainly stemming from the unpredictable complexity of tasks. With this consideration, we address the computation uncertainty by formulating a robust communication and computing resource allocation problem in ISCC systems. The primary goal of the system is to minimize total energy consumption while adhering to perception and delay constraints. This is achieved through the optimization of transmit beamforming, offloading ratio, and computing resource allocation, effectively managing the trade-offs between local execution and edge computing. To overcome this challenge, we employ a Markov decision process (MDP) in conjunction with the proximal policy optimization (PPO) algorithm, establishing an adaptive learning strategy. The proposed algorithm stands out for its rapid training speed, ensuring compliance with latency requirements for perception and computation in applications. Simulation results highlight its robustness and effectiveness within ISCC systems compared to baseline approaches. Full article

(This article belongs to the Special Issue Integrated Sensing and Communication)

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14 pages, 1181 KiB

Open AccessArticle

Multi-Functional Reconfigurable Intelligent Surfaces for Enhanced Sensing and Communication

by Khushboo Singh, Mondeep Saikia, Karthick Thiyagarajan, Dushmantha Thalakotuna, Karu Esselle and Sarath Kodagoda

Sensors 2023, 23(20), 8561; https://doi.org/10.3390/s23208561 - 18 Oct 2023

Viewed by 1439

Abstract

In this paper, we propose a reconfigurable intelligent surface (RIS) that can dynamically switch the transmission and reflection phase of incident electromagnetic waves in real time to realize the dual-beam or quad-beam and convert the polarization of the transmitted beam. Such surfaces can redirect a wireless signal at will to establish robust connectivity when the designated line-of-sight channel is disturbed, thereby enhancing the performance of wireless communication systems by creating an intelligent radio environment. When integrated with a sensing element, they are integral to performing joint detection and communication functions in future wireless sensor networks. In this work, we first analyze the scattering performance of a reconfigurable unit element and then design a RIS. The dynamic field scattering manipulation capability of the RIS is validated by full-wave electromagnetic simulations to realize six different functions. The scattering characteristics of the proposed unit element, which incorporates two p-i-n diodes have been substantiated through practical implementation. This involved the construction of a simple prototype and the subsequent examination of its scattering properties via the free-space measurement method. The obtained transmission and reflection coefficients from the measurements are in agreement with the anticipated outcomes from simulations. Full article

(This article belongs to the Special Issue Integrated Sensing and Communication)

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19 pages, 7081 KiB

Open AccessArticle

Inner-Frame Time Division Multiplexing Waveform Design of Integrated Sensing and Communication in 5G NR System

by Jian Zheng, Ping Chu, Xiaoye Wang and Zhaocheng Yang

Sensors 2023, 23(15), 6855; https://doi.org/10.3390/s23156855 - 1 Aug 2023

Cited by 3 | Viewed by 1017

Abstract

The design of an integrated sensing and communication (ISAC) waveform compatible with the 5G new radio (NR) system is crucial in enabling ISAC by utilizing the hardware of existing base stations (BSs). In this paper, we design an inner-frame time division multiplexed sensing waveform in the frame structure of 5G NR to achieve ISAC. The designed waveform is computed by the simulated annealing algorithm on an optimization cost function of a constrained combination of the peak-to-sidelobe ratio (PSLR) and the integrated sidelobe ratio (ISLR) of the velocity ambiguity function. Specifically, the constraints are the 5G communication protocol and 5G NR frame structure. In addition, we conducted corresponding signal detection and estimation methods to illustrate the performance of the sensing waveform. Both theoretical analysis and simulation experiments show that the designed waveform can effectively achieve target detection and parameter estimation under low sensing cost conditions. Full article

(This article belongs to the Special Issue Integrated Sensing and Communication)

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