Abstract
The bandwidth shortage has motivated the exploration of the millimeter wave (mmWave) frequency spectrum for future communication networks. To compensate for the severe propagation attenuation in the mmWave band, massive antenna arrays can be adopted at both the transmitter and receiver to provide large array gains via directional beamforming. To achieve such array gains, channel estimation (CE) with high resolution and low latency is of great importance for mmWave communications. However, classic super-resolution subspace CE methods such as multiple signal classification (MUSIC) and estimation of signal parameters via rotation invariant technique (ESPRIT) cannot be applied here due to RF chain constraints. In this paper, an enhanced CE algorithm is developed for the off-grid problem when quantizing the angles of mmWave channel in the spatial domain where off-grid problem refers to the scenario that angles do not lie on the quantization grids with high probability, and it results in power leakage and severe reduction of the CE performance. A new model is first proposed to formulate the off-grid problem. The new model divides the continuously-distributed angle into a quantized discrete grid part, referred to as the integral grid angle, and an offset part, termed fractional off-grid angle. Accordingly, an iterative off-grid turbo CE (IOTCE) algorithm is proposed to renew and upgrade the CE between the integral grid part and the fractional off-grid part under the Turbo principle. By fully exploiting the sparse structure of mmWave channels, the integral grid part is estimated by a soft-decoding based compressed sensing (CS) method called improved turbo compressed channel sensing (ITCCS). It iteratively updates the soft information between the linear minimum mean square error (LMMSE) estimator and the sparsity combiner. Monte Carlo simulations are presented to evaluate the performance of the proposed method, and the results show that it enhances the angle detection resolution greatly.
Highlights
Thanks to the large bandwidth available at millimeter wave frequencies, mmWave communication technology has become a promising technology to meet the experientially increasing demands of future wireless networks [1]
We study the off-grid problem and propose an enhanced method to improve the resolution of angle estimation in mmWave systems with massive antenna arrays and radio frequency (RF)
The fading weight of the path follows Rayleigh distribution with variance 1, and the continuously-valued angle of arrival (AoA)/angle of departure (AoD) are uniformly-distributed in the range [− π2, π2 )
Summary
Thanks to the large bandwidth available at millimeter wave (mmWave) frequencies, mmWave communication technology has become a promising technology to meet the experientially increasing demands of future wireless networks [1]. As adopted in IEEE 802.15.3c standard [6], a polling mechanism is employed to select the best beam vector pair from the known codebooks with p beams at the transmitter and q beams at the receiver This method consumes pq time slots to achieve angle resolution O(1/p) and O(1/q). Since the product of the number of simultaneously supported multi-users and the number of the multi-streams depends on the RF chains, it is preferable that higher angle resolution is achieved by advanced channel estimation methods to separate densely distributed users such that spatial multiplexing methods can be employed to support more users [12] In this ”off-grid” case, the gap to the theoretic lower bound is pretty large, and more antennas are required to enhance the resolution of angle estimation at the cost of more hardware and antennas [13]. We study the off-grid problem and propose an enhanced method to improve the resolution of angle estimation in mmWave systems with massive antenna arrays and RF chain constraints.
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