Analysis of Worst-Case Interference in Underlay Radar-Massive MIMO Spectrum Sharing Scenarios

Rao, Raghunandan M.; Dhillon, Harpreet S.; Marojevic, Vuk; Reed, Jeffrey H.

doi:10.1109/globecom38437.2019.9013615

Cited by 8 publications

(4 citation statements)

References 13 publications

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“…In addition, by considering the sensitivity of the radar system, the wireless communication signal may deteriorate the radar detection performance, as emphasized by [ 13 ]. In works conducted by [ 14 ], it was revealed that an average intersystem interfence at the radar system that goes from commercial base stations can be presented mathematically with a zone of exclusion. The commercial base stations’ communications systems are assumed to be equipped with many antennas, and the locations of cellular base stations are analyzed as a Poisson point process.…”

Section: Introductionmentioning

confidence: 99%

Interference Cancellation Based Spectrum Sharing for Massive MIMO Communication Systems

Miantezila

Guo

Zhang

et al. 2021

Sensors

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Cellular network operators are predicting an increase in space of more than 200 percent to carry the move and tremendous increase of total users in data traffic. The growing of investments in infrastructure such as a large number of small cells, particularly the technologies such as LTE-Advanced and 6G Technology, can assist in mitigating this challenge moderately. In this paper, we suggest a projection study in spectrum sharing of radar multi-input and multi-output, and mobile LTE multi-input multi-output communication systems near m base stations (BS). The radar multi-input multi-output and mobile LTE communication systems split different interference channels. The new approach based on radar projection signal detection has been proposed for free interference disturbance channel with radar multi-input multi-output and mobile LTE multi-input multi-output by using a new proposed interference cancellation algorithm. We chose the channel of interference with the best free channel, and the detected signal of radar was projected to null space. The goal is to remove all interferences from the radar multi-input multi-output and to cancel any disturbance sources from a chosen mobile Communication Base Station. The experimental results showed that the new approach performs very well and can optimize Spectrum Access.

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Section: Introductionmentioning

confidence: 99%

Interference Cancellation Based Spectrum Sharing for Massive MIMO Communication Systems

Miantezila

Guo

Zhang

et al. 2021

Sensors

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“…Different from spectrum sharing in communication-communication systems, in spectrum sharing in radar-communication systems, inter-system interference (ISI) has to be carefully managed because of sensitivity of radar and tremendously high transmit power of radar compared to communication system [ 20 ]. Recently, a few groups have drawn several research results on the spectrum sharing technologies between radar and communication systems [ 21 , 22 , 23 , 24 , 25 , 26 ]. The most challenging technical issue when both the radar and communication systems share the same spectrum band is obviously the inter-system interference to each other, which may significantly degrade the performance of both systems.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, the reverse direction ISI from the cellular communication system to the radar system was also not considered in [ 21 , 22 , 23 , 24 ], even though the sensitivity of the radar system is very high and the wireless communication signal may deteriorate the radar detection performance severely [ 20 ]. In [ 25 ], an average ISI at the radar system from the cellular BSs was mathematically analyzed with exclusion zone, where cellular BSs are assumed to be equipped with a massive number of antennas and the locations of cellular BSs are modeled as a Poisson point process (PPP). In [ 26 ], a chance-constrained stochastic optimization technique was proposed to guarantee the minimum performance of the radar system, while maximizing the performance of cellular system.…”

Section: Introductionmentioning

confidence: 99%

Opportunistic Interference Alignment for Spectrum Sharing between Radar and Communication Systems

Kim

Youn

Jung

2020

Sensors

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In this paper, we propose a novel opportunistic interference alignment technique for spectrum-shared radar and uplink cellular communication systems where both systems are equipped with multiple antennas. In the proposed OIA technique, the radar system sends its signal so that the radar signal is received into interference space at base stations (BSs) of the cellular system, while each uplink user (UE) generates its transmit beamforming vector so that communication signals are received within interference space at the radar receiver. Moreover, to achieve better sum-rate performance of the cellular communication system, the BS selects the UEs which results in sufficiently small interference to other cells for the uplink communication. With the proposed OIA technique, detection performance of the radar system is protected, while the communication system achieves satisfactory sum-rate performance. Through extensive computer simulations, we show that the performances of both radar and communication systems with the proposed technique significantly outperform a conventional null-space projection based spectrum sharing scheme.

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“…where propagation is dominated by the LoS component1 . In addition, the random small-scale fading amplitude satisfies E[γ i ] = 0 and E[|γ i | 2 ] = 1.…”

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confidence: 99%

Underlay Radar-Massive MIMO Spectrum Sharing: Modeling Fundamentals and Performance Analysis

Rao,

Dhillon,

Marojevic

et al. 2020

Preprint

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In this work, we investigate underlay radar-massive MIMO cellular coexistence in LoS/near-LoS channels, where both systems are capable of 3D beamforming. The cellular base station (BS) locations are modeled using a homogeneous Poisson point process (PPP), and a single radar is located at the center of a circular exclusion zone (EZ) within which the BSs are prohibited from operating. We derive an analytical expression of a tight upper bound on the average interference power at the radar due to the massive MIMO downlink. This calculation is based on a novel construction in which each Poisson Voronoi (PV) cell is bounded by its circumcircle in order to bound the effect of the random cell shapes on average interference. However, this model is intractable for characterizing the interference distribution, due to the correlation between the shapes and sizes of adjacent PV cells. Hence, we propose a tractable nominal interference model, where each PV cell is modeled as a circular disk with area equal to the average area of the typical cell. We quantify the gap in the average interference power between these two models, and show that the upper bound is tight for realistic deployment parameters.Under the nominal interference model, we derive the equal interference contour in closed-form, and characterize the interference distribution using the dominant interferer approximation. Finally, we use tractable expressions for the interference distribution to characterize important radar performance metrics such as the spatial probability of false alarm/detection in a quasi-static target tracking scenario. We validate the accuracy of our analytical approximations using numerical results, which (a) reveal useful trends in the average interference as a function of the deployment parameters (BS density, exclusion zone radius, antenna height, transmit power of each BS etc.), and (b) provide useful system design insights in the form of radar receiver operating characteristic (ROC) curves for current and future radar-cellular spectrum sharing scenarios.

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Analysis of Worst-Case Interference in Underlay Radar-Massive MIMO Spectrum Sharing Scenarios

Cited by 8 publications

References 13 publications

Interference Cancellation Based Spectrum Sharing for Massive MIMO Communication Systems

Interference Cancellation Based Spectrum Sharing for Massive MIMO Communication Systems

Opportunistic Interference Alignment for Spectrum Sharing between Radar and Communication Systems

Underlay Radar-Massive MIMO Spectrum Sharing: Modeling Fundamentals and Performance Analysis

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