Pilot Frequency Distribution in Massive MIMO Systems
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Solution Overview
Problem
In massive MIMO systems, pilot frequency pollution due to interference between users with the same pilot frequency hampers accurate state information acquisition, leading to inefficiencies in both uplink and downlink communications, and existing methods like greedy algorithms for pilot frequency distribution are complex and offer limited performance improvement.
Innovation Solution
The method divides pilot frequencies into intersecting sets Φ1, Φ2, and Φ3, categorizes users as cell central or edge based on distance to base stations, and distributes pilot frequencies accordingly, with cell edge users receiving distinct sets depending on their proximity to adjacent base stations, thereby reducing interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the number of antenna elements is increased to improve system capacity, then frequency spectrum efficiency and energy efficiency are improved, but pilot frequency pollution increases due to interference between users with the same pilot frequency
Solution Approach 1:
The patent segments the pilot frequency resources by dividing the total pilot frequency set into multiple subsets (Φ1, Φ2, Φ3) and further dividing users into different types (cell central users and cell edge users). Different user types are assigned different pilot frequency subsets, which segments the interference and reduces pilot frequency pollution while maintaining high antenna element count for improved spectrum efficiency.
Solution Approach 2:
The patent applies local quality by differentiating pilot frequency allocation based on user location characteristics. Cell central users receive one set of pilot frequencies while cell edge users receive different sets, tailored to their specific interference environments. This localized differentiation reduces pilot frequency pollution in each region while preserving the overall system capacity enabled by massive antenna elements.
2Object-affected harmful factors
If existing methods like greedy algorithms are used to distribute pilot frequencies, then pilot frequency pollution is reduced to some extent, but computational complexity increases significantly
Solution Approach 1:
The patent segments users into two simple categories (cell central and cell edge) based on distance thresholds, avoiding the need for complex greedy algorithms. This segmentation approach reduces computational complexity significantly while still achieving pilot frequency pollution reduction, as the classification and frequency allocation become straightforward deterministic rules rather than iterative optimization problems.
Solution Approach 2:
Instead of using complex algorithms to optimize pilot frequency distribution from scratch, the patent inverts the approach by pre-defining simple user categories and assigning pilot frequencies based on these categories. This inversion of the optimization process into a classification-based assignment scheme dramatically reduces computational complexity while maintaining effectiveness in reducing pilot frequency pollution.
Data Source
AI summary
The disclosure discloses a method for distributing pilot frequency in a massive antenna system, including: dividing a pilot frequency set into three sub sets that are intersecting with each other, and then dividing the users of each cell into a cell central user and a cell edge user. The cell central users use an intersection set of three pilot frequency sub sets. The cell edge users of all cells use a difference set, an intersection set and a union set of three pilot frequency sub sets according to a certain rule. When it is designing to implement the pilot resource distribution plan of the massive antenna system, three cells that are adjacent with each other in the system are used as a cluster, and a pilot frequency use plan of any one cluster may be designed according to the method proposed by the disclosure, and then the same design plan is applied to other clusters in the system, and then is adjusted according to the user distribution of each cluster and the business distribution circumstance thereof.