Hybrid Beamforming Design and Signal Processing with Fully-Connected Architecture for mmWave Integrated Sensing and Communications

Millimeter-wave (mmWave) is capable of achieving gigabit/second communication capacity and centimeter-level sensing accuracy and has become one of the main frequency bands for integrated sensing and communications (ISAC) research. Hybrid beamforming techniques have attracted much attention for solving the high path loss of mmWave and further reducing the hardware cost of the system. However, the related studies based on multicarrier and fully-connected hybrid architectures are still limited. For this reason,this paper investigates the orthogonal frequency division multiplexing (OFDM) based mmWave fully-connected hybrid architecture ISAC system to form a stable communication beam and dynamically varying sensing beam. In order to realize the aforementioned multifunctional beams, the hybrid beamformer design problem based on weighted error minimization of multicarrier is proposed and solved efficiently using the penalty dual decomposition (PDD) algorithm. Meanwhile, based on the echo model, the multicarrier multiple signal classification (MUSIC) algorithm for target angle of arrival estimation and the two-dimensional discrete Fourier transform(2D-DFT)algorithm for distance and velocity estimation are proposed, respectively. Numerical simulation results show that by adjusting the weighting factor,a flexible trade-off can be formed between the communication spectrum efficiency and the sensing accuracy error.

LoS sensing-based superimposed CSI feedback for UAV-assisted mmWave systems

In Unmanned Aerial Vehicle(UAV)-assisted millimeter Wave(mmWave)systems,Channel State Information(CSI)feedback is critical for the selection of modulation schemes,resource management,beamforming,etc.However,traditional CSI feedback methods lead to significant feedback overhead and energy consumption of the UAV transmitter,therefore shortening the system operation time.To tackle these issues,inspired by superimposed feedback and Integrated Sensing and Communications(ISAC),a Line of Sight(LoS)sensing-based superimposed CSI feedback scheme is proposed.Specifically,on the UAV transmitter side,the Ground-to-UAV(G2U)CSI is superimposed on the UAV-to-Ground(U2G)data to feed back to the ground Base Station(gBS).At the gBS,the dedicated LoS Sensing Network(LoS-SenNet)is designed to sense the U2G CSI in LoS and NLoS scenarios.With the sensed result of LoS-SenNet,the determined G2U CSI from the initial feature extraction will work as the priori information to guide the subsequent operation.Specifically,for the G2U CSI in NLoS,a CSI Recovery Network(CSI-RecNet)and superimposed interference cancellation are developed to recover the G2U CSI and U2G data.As for the LoS scenario,a dedicated LoS Aid Network(LoS-Aid Net)is embedded before the CSI-RecNet and the block of superimposed interference cancellation to highlight the feature of the G2U CSI.Compared with other methods of superimposed CSI feedback,simulation results demonstrate that the proposed feedback scheme effectively improves the recovery accuracy of the G2U CSI and U2G data.Besides,against parameter variations,the proposed feedback scheme presents its robustness.