In this paper, we propose a joint channel estimation and beamforming (BF) scheme for the wide band millimeter wave (mmWave) cellular system. Specifically, low complexity compressive sensing (CS) based estimation algorithm is used to estimate the sparse mmWave channels. Based on the estimated channel, low complexity BF scheme is proposed to adapt to the channel for data communications. The algorithm is designed by considering the practical hardware and channel constraints. Furthermore, the complexity is very low without matrix inverse and singular value decomposition (SVD) compared with traditional algorithms, which is well suitable to practical realization. Finally, we show by simulations that the performance of proposed scheme is close to the optimal scheme with extremely less overhead.

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This paper considers transmit beamforming in dual-function radar-communication (DFRC) system, where a DFRC transmitter simultaneously communicates with a communication user and detects a malicious target with the same waveform. Since the waveform is embedded with information, the information is risked to be intercepted by the target. To address this problem, physical-layer security technique is exploited. By using secrecy rate and estimation rate as performance measure for communication and radar, respectively, three secrecy rate maximization (SRM) problems are formulated, including the SRM with and without artificial noise (AN) and robust SRM. For the SRM beamforming, we prove that the optimal beamformer can be computed in closed form. For the AN-aided SRM, by leveraging alternating optimization, similar closed-form solution is obtained for the beamformer and the AN covariance matrix. Finally, the imperfect CSI of the target is also considered under the premise of a moment-based random phase-error model on the direction of arrival at the target. Simulation results demonstrate the efficacy and robustness of the proposed designs.

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