Distributed Digital Beamforming for Massive MIMO Power Reduction
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Solution Overview
Problem
Massive MIMO technology requires extensive beamforming operations, leading to high power consumption, excessive heating, and increased costs due to the need for powerful cooling systems and large antenna arrays, which also results in performance degradation due to interference from thick communication beams.
Innovation Solution
Implementing a digital beamforming system in a computationally distributed manner using multiple, less powerful processors, which splits the beamforming operation among partial digital beamforming processors, reducing the load on individual processors and enabling a more economical wireless system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized digital beamforming is implemented using powerful digital signal processors, then beamforming performance is improved, but power consumption and heat generation increase significantly
Solution Approach 1:
The patent divides the centralized digital beamforming function into multiple distributed beamforming units, each handling a subset of antenna elements. This segmentation reduces the computational burden and power consumption of each individual unit while maintaining overall beamforming performance through coordinated operation of all units.
2Measurement precision
If large antenna arrays are used to achieve precise beamforming, then communication beam precision is improved, but the size and weight of antenna towers increase
Solution Approach 1:
The large antenna array is divided into multiple smaller sub-arrays, each controlled by a separate beamforming unit. This segmentation allows the system to achieve precise beamforming through coordinated control of multiple smaller units rather than requiring a single large array, thereby reducing the weight and size requirements of individual antenna structures.
3Temperature
If powerful cooling systems are added to handle heat from beamforming processors, then thermal management is improved, but device complexity and cost increase
Solution Approach 1:
By distributing the beamforming computation across multiple smaller units, the heat generation per unit is reduced. This segmentation eliminates the need for powerful centralized cooling systems, as each unit generates less heat and can be cooled more efficiently and simply.
4Device complexity
If small antenna panels are used to reduce size and cost, then device complexity is reduced, but beamforming performance degrades due to thick communication beams and interference
Solution Approach 1:
Multiple small antenna panels are merged and coordinated through distributed beamforming control to function as a unified large array. This combining allows the system to achieve the beam precision of a large array while using smaller, less expensive panels, eliminating the performance degradation that would result from using small panels in isolation.
Data Source
AI summary
A RU for mMIMO has M antenna branches; a plurality of partial digital beamforming (PDBF) processors, each PDBF processor receiving a transmit vector comprising values for each of L data layers to be transmitted at time t from the RU via the antenna branches, wherein each of the plurality of PDBF processors performs a beamforming operation on the vector by multiplying the vector with each of a plurality of respective weight vectors that are a subset of a received weight array, to produce scalar values, each scalar value corresponding to one of the weight vectors and being supplied to a respective antenna branch; wherein the number of scalar values produced by any particular one of the PDBF processors equals the number of weight vectors used in each PDBF processor and the number of scalar values produced is equal to M; where L and M are greater than one.