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1. Effects of Beam Misalignment on Heterogeneous Cellular Networks with Mm-Wave Small Cells

   https://doi.org/10.1109/GLOBECOM48099.2022.10001400  

   Zia, Muhammad Saad ; Blough, Douglas M. ; Weitnauer, Mary Ann ( January 2022 , Proceedings of the IEEE Global Communications Conference)

   This paper studies the effects of millimeter-wave (mm-wave) beam alignment errors on the downlink achievable rate of a heterogeneous network (HetNet), which consists of sub-6 GHz macro-cells and mm-wave small-cells. The alignment error is modeled as a function of the underlying mm-wave link parameters. The conventional maximum biased received power criterion, where the bias is used for mm-wave small-cells, is adopted for cell associations. By varying the value of the bias factor, we investigate the changes in the downlink rate coverage probability. Our simulation results indicate that high values (of the order of 30 dB) for the bias, while beneficial in the case of perfect alignment, are actually disadvantageous for the low-rate users in the case of imperfect beam alignment. The low-rate users are better served by a moderate value (of the order of 20 dB) of the bias when the beam alignment errors are accounted for. We also show that the above disparity can be narrowed down by increasing by mm-wave base station (BS) antennas and/or the mm-wave BS density. 

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2. Second-Best Beam-Alignment via Bayesian Multi-Armed Bandits

   https://doi.org/10.1109/GLOBECOM38437.2019.9013578  

   Hussain, Muddassar ; Michelusi, Nicolo ( December 2019 , IEEE Global Communications Conference (GLOBECOM))

   Millimeter-wave (mm-wave) systems rely on narrow- beams to cope with the severe signal attenuation in the mm- wave frequency band. However, susceptibility to beam mis- alignment due to mobility or blockage requires the use of beam- alignment schemes, with huge cost in terms of overhead and use of system resources. In this paper, a beam-alignment scheme is proposed based on Bayesian multi-armed bandits, with the goal to maximize the alignment probability and the data-communication throughput. A Bayesian approach is proposed, by considering the state as a posterior distribution over angles of arrival (AoA) and of departure (AoD), given the history of feedback signaling and of beam pairs scanned by the base-station (BS) and the user- end (UE). A simplified sufficient statistic for optimal control is identified, in the form of preference of BS-UE beam pairs. By bounding a value function, the second-best preference policy is formulated, which strikes an optimal balance between exploration and exploitation by selecting the beam pair with the current second-best preference. Through Monte-Carlo simulation with analog beamforming, the superior performance of the second- best preference policy is demonstrated in comparison to existing schemes based on first-best preference, linear Thompson sampling, and upper confidence bounds, with up to 7%, 10% and 30% improvements in alignment probability, respectively. 

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3. High Altitude Platform Stations (HAPS): Architecture and System Performance

   Yunchou Xing, Frank Hsieh ( April 2021 , IEEE Vehicular Technology Conference)

   High Altitude Platform Station (HAPS) has the potential to provide global wireless connectivity and data services such as high-speed wireless backhaul, industrial Internet of things (IoT), and public safety for large areas not served by terrestrial networks. A unified HAPS design is desired to support various use cases and a wide range of requirements. In this paper, we present two architecture designs of the HAPS system: i) repeater based HAPS, and ii) base station based HAPS, which are both viable technical solutions. The energy efficiency is analyzed and compared between the two architectures using consumption factor theory. The system performance of these two architectures is evaluated through Monte Carlo simulations and is characterized in metrics of spectral efficiency using LTE band 1 for both single-cell and multi-cell cases. Both designs can provide good downlink spectral efficiency and coverage, while the uplink coverage is significantly limited by UE transmit power and antenna gain. Using directional antennas at the UEs can improve the system performance for both downlink and uplink. 

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4. Channel Extrapolation in FDD Massive MIMO: Theoretical Analysis and Numerical Validation

   Rottenberg, F. ; Zhang, J. ; Molisch, A. F. ( January 2019 , IEEE Globecom)

   Downlink channel estimation in massive MIMO systems is well known to generate a large overhead in frequency division duplex (FDD) mode as the amount of training generally scales with the number of transmit antennas. Using instead an extrapolation of the channel from the measured uplink estimates to the downlink frequency band completely removes this overhead. In this paper, we investigate the theoretical limits of channel extrapolation in frequency. We highlight the advantage of basing the extrapolation on high-resolution channel estimation. A lower bound (LB) on the mean squared error (MSE) of the extrapolated channel is derived. A simplified LB is also proposed, giving physical intuition on the SNR gain and extrapolation range that can be expected in practice. The validity of the simplified LB relies on the assumption that the paths are well separated. The SNR gain then linearly improves with the number of receive antennas while the extrapolation performance penalty quadratically scales with the ratio of the frequency and the training bandwidth. The theoretical LB is numerically evaluated using a 3GPP channel model and we show that the LB can be reached by practical high-resolution parameter extraction algorithms. Our results show that there are strong limitations on the extrapolation range than can be expected in SISO systems while much more promising results can be obtained in the multiple-antenna setting as the paths can be more easily separated in the delay-angle domain. 

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5. Performance Analysis of Channel Extrapolation in FDD Massive MIMO Systems

   Rottenberg, F. ; Choi, T ; Luo, P. ; Zhang, J. ; Molisch, A. F. ( January 2019 , ArXiv.org)

   Channel estimation for the downlink of frequency division duplex (FDD) massive MIMO systems is well known to generate a large overhead as the amount of training generally scales with the number of transmit antennas in a MIMO system. In this paper, we consider the solution of extrapolating the channel frequency response from uplink pilot estimates to the downlink frequency band, which completely removes the training overhead. We first show that conventional estimators fail to achieve reasonable accuracy. We propose instead to use high-resolution channel estimation. We derive theoretical lower bounds (LB) for the mean squared error (MSE) of the extrapolated channel. Assuming that the paths are well separated, the LB is simplified in an expression that gives considerable physical insight. It is then shown that the MSE is inversely proportional to the number of receive antennas while the extrapolation performance penalty scales with the square of the ratio of the frequency offset and the training bandwidth. The channel extrapolation performance is validated through numeric simulations and experimental measurements taken in an anechoic chamber. Our main conclusion is that channel extrapolation is a viable solution for FDD massive MIMO systems if accurate system calibration is performed and favorable propagation conditions are present. 

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