Performance Analysis of Joint Radar and Communication using OFDM and OTFS

Gaudio, Lorenzo; Kobayashi, Mari; Bissinger, Björn; Caire, Giuseppe

doi:10.48550/arxiv.1902.01184

Cited by 1 publication

(2 citation statements)

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“…where r = x − y , G is the transmit antenna gain, h 0 (τ ) denotes the channel power gain of the link between the BS and the object during time slot τ , A is the radar cross-section area of the object, A e is the effective area i.e., A e = G c 2 4πf 2 , where c is the speed of light and f is the carrier frequency, and = (c/4πf ) 2 . Then, by focusing on a particular time slot, the signal-to-interference-plus-noise ratio (SINR) of the reflected pilot sequence, is given by…”

Section: Detection Modelmentioning

confidence: 99%

“…E MERGING applications such as smart cars, unmanned aerial vehicles (UAV) and enhanced localization, lead to an ever-increasing demand for systems with both communication and radar sensing capabilities [1], [2]. In order to address this demand, joint communication and radar sensing (JCAS) techniques have been developed, integrating the two operations of communication and sensing over a shared spectrum.…”

Section: Introductionmentioning

confidence: 99%

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FD-JCAS Techniques for mmWave HetNets: Ginibre Point Process Modeling and Analysis

Skouroumounis¹,

Psomas²,

Krikidis³

2021

Preprint

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In this paper, we study the co-design of full-duplex (FD) radio with joint communication and radar sensing (JCAS) techniques in millimeter-wave (mmWave) heterogeneous networks (HetNets). Spectral co-existence of radar and communication systems causes mutual interference between the two systems, compromising both the data exchange and sensing capabilities. Focusing on the detection performance, we propose a cooperative detection technique, which exploits the sensing information from multiple base stations (BSs), aiming at enhancing the probability of successfully detecting an object. Three combining rules are considered, namely the OR, the Majority and the AND rule. In real-world network scenarios, the locations of the BSs are spatially correlated, exhibiting a repulsive behavior. Therefore, we model the spatial distribution of the BSs as a β-Ginibre point process (β-GPP), which can characterize the repulsion among the BSs. By using stochastic geometry tools, analytical expressions for the detection performance of β-GPP-based FD-JCAS systems are expressed for each of the considered combining rule. Furthermore, by considering temporal interference correlation, we evaluate the probability of successfully detecting an object over two different time slots. Our results demonstrate that our proposed technique can significantly improve the detection performance when compared to the conventional non-cooperative technique.

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Section: Detection Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%