An Overview of Low-Rank Channel Estimation for Massive MIMO Systems
Hongxiang Xie,Feifei Gao,Shi Jin +2 more
TLDR
A general overview of the current low-rank channel estimation approaches is provided, including their basic assumptions, key results, as well as pros and cons on addressing the aforementioned tricky challenges.Abstract:
Massive multiple-input multiple-output is a promising physical layer technology for 5G wireless communications due to its capability of high spectrum and energy efficiency, high spatial resolution, and simple transceiver design. To embrace its potential gains, the acquisition of channel state information is crucial, which unfortunately faces a number of challenges, such as the uplink pilot contamination, the overhead of downlink training and feedback, and the computational complexity. In order to reduce the effective channel dimensions, researchers have been investigating the low-rank (sparse) properties of channel environments from different viewpoints. This paper then provides a general overview of the current low-rank channel estimation approaches, including their basic assumptions, key results, as well as pros and cons on addressing the aforementioned tricky challenges. Comparisons among all these methods are provided for better understanding and some future research prospects for these low-rank approaches are also forecasted.read more
Citations
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Journal ArticleDOI
Deep Generative Models for Downlink Channel Estimation in FDD Massive MIMO Systems
TL;DR: In this paper , a deep generative model (DGM)-based technique was proposed to estimate the frequency-independent underlying channel parameters, i.e., the magnitudes of path gains, delays, angles-of-arrivals (AoAs) and angles of departure and arrival, via uplink training, since these parameters are common in both uplink and downlink.
Proceedings ArticleDOI
Pilot reuse with a large number of antennas: Performance analysis and pilot contamination reduction
TL;DR: The normalized mean square error (NMSE) of the minimum meansquare error (MMSE) channel estimation algorithm in the presence of pilot contamination is investigated, and an effective uplink training strategy with silent cell is proposed by carefully designing a sophisticated uplinkTraining.
Proceedings ArticleDOI
Low-complexity detection for multi-antenna differential unitary space-time modulation systems
TL;DR: A new low-complexity sphere detection algorithm is proposed for differential unitary space-time modulation systems with multiple antennas to constraint the searching radius of the sphere by a heuristic SNR-dependent factor.
Posted Content
Interference-Alignment and Soft-Space-Reuse Based Cooperative Transmission for Multi-cell Massive MIMO Networks
TL;DR: An IA and soft-space-reuse (IA-SSR)-based cooperative transmission scheme under the two-stage precoding framework with separately treated cell-center and cell-edge users separately treated to fully exploit the spatial degrees of freedoms.
Proceedings ArticleDOI
AoD-Adaptive Channel Feedback in FDD Massive MIMO Systems with Multiple-Antenna Users
TL;DR: This paper designs feedback codebooks based on optimal subspace packing in the Grassmannian manifold and quantifies the rate gap between the rate of the system with perfect Channel State Information at the massive MIMO Basestation (BS) and the proposed channel feedback scheme for a given number of feedback bits.
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