Angle Of Departure Estimation Research Articles

Training Beam Sequence Design for mmWave Tracking Systems With and Without Environmental Knowledge

In this paper, we consider a millimeter wave multiple-input single-output tracking system, where the time-varying angle of departure (AoD) is assumed to change following a discrete state Markov process. Depending on whether the associated AoD transition function is available or not, we propose two different training beam sequence design approaches. Specifically, in the case when the AoD transition function is available, we leverage the maximum a posteriori criterion to estimate the updated AoD in each beam tracking period. Since it is infeasible to derive an explicit expression for the resultant estimation error rate, we turn to its upper bound, which possesses a closed-form expression and is therefore used as the objective function to optimize the training beam sequence. Considering the complicated objective function and the unit modulus constraints imposed by the analog phase shifters, we resort to a particle swarm algorithm to solve the formulated optimization problem. In the case when the AoD transition function is unavailable, we turn to the maximum likelihood criterion for AoD estimation. To cope with the unknown AoD transition function, we reformulate the beam tracking problem as a partially observable Markov decision process problem and develop an actor-critic reinforcement learning framework to obtain an efficient training beam sequence design. Numerical results demonstrate superiorities of the proposed training beam sequence design approaches for both two cases.

Novel AoD Estimation Algorithms for WSSUS and Non-WSSUS V2V Channel Modeling

In this paper, we propose efficient computational solutions for estimating the statistical properties of wide-sense stationary un-correlative scattering (WSSUS) and non-WSSUS multiple-input multiple-output (MIMO) vehicle-to-vehicle (V2V) channel models. Specifically, in the WSSUS channel models, we first estimate the angle of departure (AoD) for the non-line of sight (NLoS) propagation components. In this manner, the complex channel impulse response (CIR), which are widely used in the existing literature to characterize the wireless channel physical properties, can be estimated on the basis of the estimated AoD and defined model parameters. Conversely, in the non-WSSUS channel models, by estimating the AoD in the initial stage, the real-time complex CIR of the V2V channel model can be estimated on the basis of the estimated AoD and the moving time/velocities/directions of the mobile transmitter (MT) and mobile receiver (MR). In the estimation process of the aforementioned cases, we introduce different solutions to convert the CIRs from the complex domain to the real-value domain, thereby optimizing the computational efficiency for investigating channel characteristics as compared to existing methods. Numerical results of the WSSUS and non-WSSUS MIMO V2V channel characteristics, such as the spatial-temporal (ST) cross-correlation functions (CCFs) and auto-correlation functions (ACFs), are estimated on the basis of the estimated complex CIRs. These results are in agreements with theoretical ones, indicating that the proposed algorithms are practical for estimating the WSSUS and non-WSSUS MIMO V2V channel characteristics.

Cell ID and Angle of Departure Estimation for Millimeter-wave Cellular Systems in Line-of-Sight Dominant Conditions Using Zadoff-Chu Sequence Based Beam Weight

Millimeter-wave (mmWave) bands is considered for fifth-generation (5G) cellular systems because abundant spectrum is available for mobile broadband communications. In mmWave communication systems, accurate beamforming is important to compensate for high attenuation in the mmWave frequency band and to extend the transmission range. However, with the existing beamformers in mmWave cellular systems, the mobile station (MS) cannot identify the source (base station; BS) of the received beam because there are many neighboring BSs transmitting their training signals, requiring a large overhead. This paper proposes a new beam weight generation method for transmitting (Tx) beamformers at the BS in mmWave cellular systems during a beam training period. Beam weights are generated for Tx beamformers at neighboring BSs, so that a mobile station (MS) can estimate the source (cell ID; CID) and angle of departure (AoD) for each BS in multi-cell environments. A CID and AoD estimation method for mmWave cellular systems in a line-of-sight (LOS) dominant condition is presented using the beam weights generated by Zadoff-Chu sequence. A simulation is conducted in a LOS dominant condition to show that the performances of CID detection and AoD estimation are similar for both the proposed and conventional methods. In the conventional methods, the DFT-based beamforming weight is used for Tx beamformer at the BS and orthogonal matching pursuit (OMP) algorithm is used for AoD estimation at the MS. The proposed method significantly reduces the processing time (1.6–6.25%) required for beam training compared to the conventional method.

EKF-Based Beam Tracking for mmWave MIMO Systems

Beam tracking is an effective way to maintain high-quality links in mobile millimeter wave MIMO systems, which is achieved by accurately estimating angle-of-departure (AoD) and angle-of-arrival (AoA) of the desired path. Considering the slow variations of angular velocity for time-varying AoD and AoA, a second-order AoD/AoA variation model is proposed for extended Kalman filter (EKF) based beam tracking. By utilizing two well configured tracking beam pairs, the unknown path gain is removed from EKF’s measurement model and the optimal estimation of AoD/AoA is derived. Simulation results demonstrate that the proposed EKF-based beam tracking method achieves higher AoD estimation accuracy than previous methods.

Channel Estimation For Mimo-Ofdm Systems of Joint Angle-of-Departure (AOD) or Angle-of-Arrival (AOA)

Beamforming with gathering mechanical assembly displays has been considered as an engaging advancement in future remote correspondence structures. To coordinate beamforming, one has to know the angle-of-departure (AoD) or angle-of-arrival (AoA). For data disclosure, the beneficiary in like manner has to know station response. In this paper, we propose another joint AoD, AoA, and channel estimation contrive for pilot-helped MIMO-OFDM systems. Starting, a compressive distinguishing system is used to survey the channel drive response, abusing the sparsity property of remote channels. By then, AoA and AoD are as one surveyed for each perceived path by the most maximum likelihood (ML) procedure. The successive Cramer-Rao lower bound (SCRLB) is moreover gathered and a transmit beamforming plan is proposed as necessities be. In the circumstance of available prior information, a most outrageous a posteriori estimation is proposed. Amusement results exhibit that the proposed procedures can approach the SCRLB achieve a comparable supernatural viability as that got with the ideal direct in millimetre-wave correspondences. the SCRLB is low multifaceted nature computation and to constrain misstep rate and improve sign to fuss extent.

Joint AoD, AoA, and Channel Estimation for MIMO-OFDM Systems

Beamforming with antenna arrays has been considered as an enabling technology in future wireless communication systems. To conduct beamforming, one has to know the angle-of-departure (AoD) or angle-of-arrival (AoA). For data detection, the receiver also has to know channel response. In this paper, we propose a new joint AoD, AoA, and channel estimation scheme for pilot-assisted multiple-input-multiple-output–orthogonal-frequency-division-multiplexing (MIMO-OFDM) systems. First, a compressive-sensing technique is employed to estimate the channel impulse response, exploiting the sparsity property of wireless channels. Then, AoA and AoD are jointly estimated for each detected path by the maximum likelihood method. The Cramer–Rao lower bound (CRLB) is also derived and a transmit beamforming scheme is proposed accordingly. In the scenario of available prior information, a maximum a posteriori estimation is proposed. The Bayesian CRLB (BCRLB) for the problem is also derived and a transmit beamforming scheme is further proposed. It turns out that only two training OFDM symbols are required for the estimation. Simulation results show that the proposed methods can approach the CRLB/BCRLB in both scenarios and achieve the same spectral efficiency as that obtained with the ideal channel in millimeter-wave communications.

Two-Dimensional AoD and AoA Acquisition for Wideband Millimeter-Wave Systems With Dual-Polarized MIMO

In this paper, a novel two-dimensional super-resolution angle-of-departure (AoD) and angle-of-arrival (AoA) estimation technique is proposed for wideband millimeter-wave multiple-input multiple-output systems with dual-polarized antenna elements. The key ingredient of the proposed method is the custom designed beam pairs, from which there exists an invertible function of the AoD/AoA. A new multi-layer reference signal structure is developed for the proposed method to facilitate angle estimation for wideband channels with dual-polarized antenna elements. To reduce feedback in closed-loop frequency division duplexing systems, a novel differential feedback strategy is proposed to feedback the estimated angle pairs. Numerical results demonstrate that good azimuth/elevation AoD and AoA estimation performance can be achieved under different levels of signal-to-noise ratio, channel conditions, and antenna array configurations.

Auxiliary Beam Pair Enabled AoD and AoA Estimation in Closed-Loop Large-Scale Millimeter-Wave MIMO Systems

Channel estimation is of critical importance in millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems. Due to the use of large antenna arrays, low-complexity mmWave specific channel estimation algorithms are required. In this paper, an auxiliary beam pair design is proposed to provide high-resolution estimates of the channel’s angle-of-departure (AoD) and angle-of-arrival (AoA) for mmWave MIMO systems. By performing an amplitude comparison with respect to each auxiliary beam pair, a set of ratio measures that characterize the channel’s AoD and AoA are obtained by the receiver. Either the best ratio measure or the estimated AoD is quantized and fed back to the transmitter via a feedback channel. The proposed technique can be incorporated into control channel design to minimize initial access delay. Though the design principles are derived assuming a high-power regime, evaluation under more realistic assumption shows that by employing the proposed method, good angle estimation performance is achieved under various signal-to-noise ratio levels and channel conditions.

A distributed localization in wireless sensor networks utilizing AOD estimation and synthetical uniform circular array

The localization of wireless sensor nodes is one of the key technologies in wireless sensor networks (WSN). Recently, a distributed localization method has been proposed based on a novel concept of angle of departure (AOD) estimation, which can be employed by e.g., the single antenna sensors to estimate the angle information and achieve localization. Based on the AOD estimation, in this paper, we introduce a synthetic uniform circular array (SUCA) synthesized by a rotary antenna on anchor to get the distributed localization of the sensors in multi-path environments. The rotated operation of antenna could create the SUCA with a larger aperture to deal with AOD of multipath components (MPCs) and relax the condition that array aperture should be greater than the number of MPCs. This new localization method only relies on radio transceivers without requiring extra measuring equipments, and the sensor nodes conduct localization in a completely distributed manner instead of centralized processing, which is suitable for large-scale WSN. Meanwhile, the influence of carrier frequency offset (CFO) between the transceivers is also considered and it is eliminated by utilizing the signal emitted from an auxiliary antenna.