Beamspace maximum likelihood algorithm based on sum and difference beams for elevation estimation

Beamspace super-resolution methods for elevation estimation in multipath environment has attracted significant attention, especially the beamspace maximum likelihood(BML)algorithm. However, the difference beam is rarely used in superresolution methods, especially in low elevation estimation. The target airspace information in the difference beam is different from the target airspace information in the sum beam. And the use of difference beams does not significantly increase the complexity of the system and algorithms. Thus, this paper applies the difference beam to the beamformer to improve the elevation estimation performance of BML algorithm. And the direction and number of beams can be adjusted according to the actual needs. The theoretical target elevation angle root means square error(RMSE) and the computational complexity of the proposed algorithms are analyzed. Finally, computer simulations and real data processing results demonstrate the effectiveness of the proposed algorithms.

Adaptive transmit beamspace optimization design based on RD-log-FDA radar

Because of the range-angle dependency in random log frequency diverse array(RD-log-FDA) radar, a method for designing beamspace transformation matrix in angle and range based on the receive signal has been proposed.It is demonstrated that the designed beamspace transformation matrix basically meets the requirements of beam gain.However, there are some problems in the transformation matrix designed, such as unstable beam gain and high sidelobe.Hence, we propose an optimization method by adjusting array element spacing and random number in frequency offset to get the optimum beam gain.Therefore, particle swarm optimization(PSO) is used to find the optimal solution.The beam gain comparison before and after the optimization is obtained by simulation, and the results show that the optimized array after beamspace preprocessing has more stable beam gain, lower sidelobe, and higher resolution in parameter estimation.In conclusion, the RD-log-FDA is capable of forming desired beam gain in angle and distance through beamspace preprocessing, and suppressing interference signals in other areas.

Fingerprint-Based Millimeter-Wave Beam Selection for Interference Mitigation in Beamspace Multi-User MIMO Communications

Millimeter-wave communications are suitable for application to massive multiple-input multiple-output systems in order to satisfy the ever-growing data traffic demands of the next-generation wireless communication.However,their practical deployment is hindered by the high cost of complex hardware,such as radio frequency(RF)chains.To this end,operation in the beamspace domain,through beam selection,is a viable solution.Generally,the conventional beam selection schemes focus on the feedback and exhaustive search techniques.In addition,since the same beam in the beamspace may be assigned to a different user,conventional beam selection schemes suffer serious multi-user interference.In addition,some RF chains may be wasted,since they do not contribute to the sum-rate performance.Thus,a fingerprint-based beam selection scheme is proposed to solve these problems.The proposed scheme conducts offline group-based fingerprint database construction and online beam selection to mitigate multi-user interference.In the offline phase,the contributing users with the same best beam are grouped.After grouping,a fingerprint database is created for each group.In the online phase,beam selection is performed for purposes of interference mitigation using the information contained in the group-based fingerprint database.The simulation results confirm that the proposed beam selection scheme can achieve a signal-to-interference-plus-noise ratio and sum-rate performance which is close to those of a fully digital system,and having much higher energy efficiency.

Angle Estimation in Monostatic MIMO Radar with Low-Complexity Beamspace Unitary ESPRIT

A low-complexity angle estimation method for multiple-input multiple-output(MIMO) radar using beamspace unitary estimation of signal parameters via rotational invariance techniques(ESPRIT) is presented.Reduced-dimensional transformation is firstly utilized as a pre-processing to obtain the reduced-dimensional data matrix, and then a conjugate centrosymmetric discrete Fourier transform(DFT) matrix is employed to map the received data into lower-dimensional beamspace and transforms the complex covariance matrix into a realvalued one. At last, the rotational invariance structure of the real-valued signal subspace is constructed in the beamspace to obtain the estimation of direction of arrival(DOA). Compared with the other ESPRIT algorithms,the proposed method can achieve improved estimation performance with a significantly reduced computational complexity. Simulation results are presented to demonstrate the effectiveness of the proposed method.