Abstract
Fifth generation (5G) cellular standards are set to utilize millimeter wave (mmWave) frequencies, which enable data speeds greater than 10 Gbps and sub-centimeter localization accuracy. These capabilities rely on accurate estimates of the channel parameters, which we define as the angle of arrival, angle of departure, and path distance for each path between the transmitter and receiver. Estimating the channel parameters in a computationally efficient manner poses a challenge because it requires estimation of parameters from a high-dimensional measurement – particularly for multi-carrier systems since each subcarrier must be estimated separately. Additionally, channel parameter estimation must be able to handle hybrid beamforming, which uses a combination of digital and analog beamforming to reduce the number of required analog to digital converters. This paper introduces a channel parameter estimation technique based on the multilinear singular value decomposition (MSVD), a Tucker form tensor analog of the singular value decomposition, for massive multiple input multiple output (MIMO) multi-carrier systems with hybrid beamforming. The MSVD tensor estimation approach is more computationally efficient than methods such as the canonical polyadic decomposition (CPD) and the Tucker form of the MSVD enables paths to be extracted based on signal energy. The algorithms performance is compared to the CPD method and shown to closely match the Cramer-Rao bound (CRB) of channel parameter estimates through simulations. Additionally, limitations of channel parameter estimation and communication waveform effects are studied.
Highlights
Fifth generation (5G) cellular networks are set to deploy millimeter wave technology with carrier frequencies ranging from 30 GHz to 300 GHz [1]
High performance communication and localization for mmWave technology are both dependent on accurate estimates of the channel parameters, which we define as the angle of arrival (AOA), angle of departure (AOD), and total transmitter to receiver path distance for each significant path
Our results show that the multilinear singular value decomposition (MSVD) technique closely matches the Cramer-Rao bound (CRB) and canonical polyadic decomposition (CPD) method
Summary
Fifth generation (5G) cellular networks are set to deploy millimeter wave (mmWave) technology with carrier frequencies ranging from 30 GHz to 300 GHz [1]. MmWave non-line of sight (NLOS) paths are not treated as interference, but rather as additional paths that carry useful information [4], [27] This enables the reflection locations to be estimated from the channel parameters; making simultaneous localization and mapping (SLAM) possible, where the receiver is localized while the environment is mapped in parallel [9], [26]. The work in [35] shows that OFDM MIMO receiver measurements fit a low rank tensor form and channel parameter estimation is achieved by estimating a best-fit CPD tensor. Our results show that the MSVD technique closely matches the CRB and CPD method Another advantage of the Tucker form and MSVD estimation method over the CPD method is that it offers a simple method to estimate the channel rank and number of paths.
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