40 research outputs found
A Survey of Beam Management for mmWave and THz Communications Towards 6G
Communication in millimeter wave (mmWave) and even terahertz (THz) frequency
bands is ushering in a new era of wireless communications. Beam management,
namely initial access and beam tracking, has been recognized as an essential
technique to ensure robust mmWave/THz communications, especially for mobile
scenarios. However, narrow beams at higher carrier frequency lead to huge beam
measurement overhead, which has a negative impact on beam acquisition and
tracking. In addition, the beam management process is further complicated by
the fluctuation of mmWave/THz channels, the random movement patterns of users,
and the dynamic changes in the environment. For mmWave and THz communications
toward 6G, we have witnessed a substantial increase in research and industrial
attention on artificial intelligence (AI), reconfigurable intelligent surface
(RIS), and integrated sensing and communications (ISAC). The introduction of
these enabling technologies presents both open opportunities and unique
challenges for beam management. In this paper, we present a comprehensive
survey on mmWave and THz beam management. Further, we give some insights on
technical challenges and future research directions in this promising area.Comment: accepted by IEEE Communications Surveys & Tutorial
Separate DOD and DOA Estimation for Bistatic MIMO Radar
A novel MUSIC-type algorithm is derived in this paper for the direction of departure (DOD) and direction of arrival (DOA) estimation in a bistatic MIMO radar. Through rearranging the received signal matrix, we illustrate that the DOD and the DOA can be separately estimated. Compared with conventional MUSIC-type algorithms, the proposed separate MUSIC algorithm can avoid the interference between DOD and DOA estimations effectively. Therefore, it is expected to give a better angle estimation performance and have a much lower computational complexity. Meanwhile, we demonstrate that our method is also effective for coherent targets in MIMO radar. Simulation results verify the efficiency of the proposed method, particularly when the signal-to-noise ratio (SNR) is low and/or the number of snapshots is small
Robust Target Positioning for Reconfigurable Intelligent Surface Assisted MIMO Radar Systems
The direction of arrival (DOA) based multiple-input multiple-output (MIMO) radar technique has been widely utilized for ubiquitous positioning due to its advantage of simple implementability. On the other hand, reconfigurable intelligent surface (RIS) has received considerable attention, which can be deployed on the walls and objects to strengthen the positioning performance. However, RIS is usually not equipped with a perception module, which results in the tremendous challenge for RIS-assisted positioning. To tackle this challenge, this paper propose the fundamental problem of DOA-based target positioning in RIS-assisted MIMO radar system. Unlike conventional DOA estimation systems, the beneficial role of RIS is investigated in MIMO radar system, where a nonconvex promoting function is exploited to estimate DOA task. By adjusting the reflecting elements of the RIS, the proximal projection iterative strategy is developed to obtain the feasible solution. Both theoretical analysis and simulation results illustrate that the proposed scheme can achieve remarkable positioning performance and shed light on the benefits offered by the adoption of the RIS in terms of positioning performance
Spatial Parameter Identification for MIMO Systems in the Presence of Non-Gaussian Interference
Reliable identification of spatial parameters for multiple-input multiple-output (MIMO) systems, such as the number of transmit antennas (NTA) and the direction of arrival (DOA), is a prerequisite for MIMO signal separation and detection. Most existing parameter estimation methods for MIMO systems only consider a single parameter in Gaussian noise. This paper develops a reliable identification scheme based on generalized multi-antenna time-frequency distribution (GMTFD) for MIMO systems with non-Gaussian interference and Gaussian noise. First, a new generalized correlation matrix is introduced to construct a generalized MTFD matrix. Then, the covariance matrix based on time-frequency distribution (CM-TF) is characterized by using the diagonal entries from the auto-source signal components and the non-diagonal entries from the cross-source signal components in the generalized MTFD matrix. Finally, by making use of the CM-TF, the Gerschgorin disk criterion is modified to estimate NTA, and the multiple signal classification (MUSIC) is exploited to estimate DOA for MIMO system. Simulation results indicate that the proposed scheme based on GMTFD has good robustness to non-Gaussian interference without prior information and that it can achieve high estimation accuracy and resolution at low and medium signal-to-noise ratios (SNRs)