Joint System Design for Coexistence of MIMO Radar and MIMO Communication

Qian, Junhui; Lops, Marco; Zheng, Li; Wang, Xiaodong; He, Zishu

doi:10.1109/tsp.2018.2831624

Cited by 200 publications

(111 citation statements)

References 43 publications

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“…In order to study the clutter effect on the massive MIMO system, we start evaluating the clutter covariance matrix of the whole clutter-related observable c. To this end, we assume to have N s scatterers, each contributing Q replicas of the radar signal in the packet under test. Under these circumstances, and using the definitions in (11) and (13), the clutter matrix in the packet under test can be written as…”

Section: Information Theoretic Analysismentioning

confidence: 99%

Communications and Radar Coexistence in the Massive MIMO Regime: Uplink Analysis

D’Andrea

Buzzi

Lops

2020

IEEE Trans. Wireless Commun.

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This paper considers the uplink of a massive MIMO communication system using 5G New Radio-compliant multiple access, which is to co-exist with a radar system using the same frequency band. A system model taking into account the reverberation (clutter) produced by the radar system onto the massive MIMO receiver is proposed. In this scenario, several receivers for uplink channel estimation and data detection are proposed, ranging from the simple channel-matched beamformer to the zero-forcing and linear minimum mean square error receivers for clutter disturbance rejection, under the two opposite situations of perfectly known ad completely unknown clutter covariance. A theoretical analysis is also given, deriving a lower bound on the achievable uplink spectral efficiency and the mutual information between the input Gaussian-encoded symbols and the observables available at the communication receiver of the cellular massive MIMO system: regarding the latter, in particular, we show that, in the large antenna number regime, the radar clutter effects at the base station is suppressed and single-user capacity is restored. Numerical results, illustrating the performance of the proposed detection schemes, confirm the findings of the theoretical analysis, and permit quantifying the system robustness to clutter effect for increasing number of antennas at the base station.

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Section: Information Theoretic Analysismentioning

confidence: 99%

Communications and Radar Coexistence in the Massive MIMO Regime: Uplink Analysis

D’Andrea

Buzzi

Lops

2020

IEEE Trans. Wireless Commun.

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“…In this case, the work period of the MIMO radar is reduced from QT PRI to P T PRI , which significantly cuts down the energy consumption and lowers the probability of interception in a hostile environment. During the period of (Q − P )T P RI when no pulse is sent out, the radar can work in other modes, which enables multi-function radar [51,52]. With the RTT technique, the received data will be {Ỹ q } q∈Ω p .…”

Section: One-bit Mimo Radarmentioning

confidence: 99%

Gridless Parameter Estimation for One-Bit MIMO Radar With Time-Varying Thresholds

Xiang

Chen

et al. 2020

IEEE Trans. Signal Process.

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We investigate the one-bit MIMO (1b-MIMO) radar that performs one-bit sampling with a timevarying threshold in the temporal domain and employs compressive sensing in the spatial and Doppler domains. The goals are to significantly reduce the hardware cost, energy consumption, and amount of stored data. The joint angle and Doppler frequency estimations from noisy one-bit data are studied.By showing that the effect of noise on one-bit sampling is equivalent to that of sparse impulsive perturbations, we formulate the one-bit ℓ 1 -regularized atomic-norm minimization (1b-ANM-L1) problem to achieve gridless parameter estimation with high accuracy. We also develop an iterative method for solving the 1b-ANM-L1 problem via the alternating direction method of multipliers. The Cramér-Rao bound (CRB) of the 1b-MIMO radar is analyzed, and the analytical performance of one-bit sampling with two different threshold strategies is discussed. Numerical experiments are presented to show that the 1b-MIMO radar can achieve high-resolution parameter estimation with a largely reduced amount of data.

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“…In both iterative algorithms, i.e., 'Iter + ML' and 'Iter + Greedy', the maximum numbers of iterations is i max = 10. The initial estimate of the matrix A is computed via (23).…”

Section: B Decoding Strategiesmentioning

confidence: 99%

“…The work [20] proposed a scheme based on generalized spatial modulation (GSM) [21], in which some of the information bits are conveyed in the selection of the antennas utilized for communication. The drawback of these previous DFRC methods, particularly when radar is the primary functionality, is that communication interferes with the radar, either via spectral interference, power sharing, or by reducing the number of available antennas, resulting in an inherent tradeoff between radar and communication performance [22], [23].…”

Section: Introductionmentioning

confidence: 99%

A Dual-Function Radar Communication System Using Index Modulation

Huang

Liu

et al. 2019

2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

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Dual-function radar communication (DFRC) systems implement both sensing and communication using the same hardware. Such schemes are often more efficient in terms of size, power, and cost, over using distinct radar and communication systems. Since these functionalities share resources such as spectrum, power, and antennas, DFRC methods typically entail some degradation in both radar and communication performance. In this work we propose a DFRC scheme based on the carrier agile phased array radar (CAESAR), which combines frequency and spatial agility. The proposed DFRC system, referred to as multi-carrier agile joint radar communication (MAJoRCom), exploits the inherent spatial and spectral randomness of CAESAR to convey digital messages in the form of index modulation. The resulting communication scheme naturally coexists with the radar functionality, and thus does not come at the cost of reduced radar performance. We analyze the performance of MAJoRCom, quantifying its achievable bit rate. In addition, we develop a low complexity decoder and a codebook design approach, which simplify the recovery of the communicated bits. Our numerical results demonstrate that MAJoRCom is capable of achieving a bit rate which is comparable to utilizing independent communication modules without affecting the radar performance, and that our proposed low-complexity decoder allows the receiver to reliably recover the transmitted symbols with an affordable computational burden. arXiv:1909.04223v1 [eess.SP]

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Joint System Design for Coexistence of MIMO Radar and MIMO Communication

Cited by 200 publications

References 43 publications

Communications and Radar Coexistence in the Massive MIMO Regime: Uplink Analysis

Communications and Radar Coexistence in the Massive MIMO Regime: Uplink Analysis

Gridless Parameter Estimation for One-Bit MIMO Radar With Time-Varying Thresholds

A Dual-Function Radar Communication System Using Index Modulation

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