Large Scalable Antenna System Pilot Contamination Mitigation
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Solution Overview
Problem
Large Scalable Antenna Systems face pilot contamination issues due to the limited number of orthogonal uplink pilot sequences, leading to contaminated Channel State Information and interference in multi-cellular systems, with existing methods providing suboptimal solutions.
Innovation Solution
The method involves partitioning the Large Scalable Antenna System into sub-arrays with precoding vectors generating beams pointing in different directions, allowing for the reuse of uplink pilot sequences without significant contamination, and estimating Channel State Information using these sub-arrays to generate enhanced CSI by combining sub-array CSI with antenna array geometry and beam patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If uplink pilot sequences are reused from one cell to another to increase the number of available pilots, then the number of supported terminals increases, but pilot contamination occurs causing contaminated Channel State Information and interference
Solution Approach 1:
The antenna array is divided into multiple sub-arrays, each independently estimating channel state information from pilot sequences. This segmentation allows the system to process pilot signals from different spatial regions separately, enabling pilot reuse across cells while mitigating contamination through spatial differentiation.
Solution Approach 2:
Each sub-array is configured with specific beamforming weights to focus on local spatial regions. By making the channel estimation quality spatially dependent on the sub-array location and beam direction, the system can distinguish between desired pilot signals and contaminated signals from other cells, allowing safe pilot reuse.
2Quantity of substance
If the number of orthogonal uplink pilot sequences is increased to support more terminals, then more terminals can be served simultaneously, but the coherence interval duration limits the maximum number of orthogonal sequences
Solution Approach 1:
The system transitions from relying solely on temporal orthogonality (time-domain pilot sequences) to utilizing spatial orthogonality through sub-array beamforming. By adding the spatial dimension to pilot differentiation, the system can support more terminals than the time-coherence interval would normally allow, effectively increasing the number of usable pilot sequences.
3Ease of manufacture
If traditional channel estimation methods are used in multi-cell systems with pilot reuse, then implementation is simple, but contaminated Channel State Information leads to directed interference to terminals sharing the same pilot sequence
Solution Approach 1:
The channel estimation process is segmented across multiple sub-arrays, each performing independent estimation with its own beamforming weights. This segmentation transforms the complex problem of multi-cell channel estimation with contamination into multiple simpler parallel estimations that can be combined, maintaining implementation simplicity while reducing interference through spatial filtering.
Data Source
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AI summary
A method and Base station for Channel State Information estimation in a wireless network is proposed. The wireless network comprises at least one base station. The at least one base station comprises a Large Scalable Antenna System. The Large Scalable Antenna System antenna elements are partitioned in sub-arrays. Precoding vectors for each sub-array are generated such that the antenna beams of the sub-arrays point to different directions. At least one uplink pilot sequence is received by at least one antenna sub-array. A Channel State Information is estimated for the at least one antenna sub-array based on the received pilot sequence. The Channel State Information estimated for at least one antenna sub-array is extrapolated to the antenna elements of the Large Scalable Antenna System.