Distributed Precoding Estimates in Distributed Antenna Systems
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Solution Overview
Problem
In distributed antenna systems, centralized precoding for remote radio heads (RRHs) requires significant communication channel overhead due to the need for channel feedback from all RRHs to the base station controller, which becomes prohibitive in massive MIMO architectures.
Innovation Solution
Implementing distributed computation of precoding estimates within each RRH, where each RRH determines intra-RRH interference precoding using its channel estimates and communicates only the derived inter-RRH interference precoding parts back to the base station controller, reducing the need for channel information exchange and minimizing communication overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized precoding is performed at the base station controller, then interference cancellation between RRHs is achieved, but communication channel overhead becomes prohibitive due to requiring channel feedback from all RRHs
Solution Approach 1:
The precoding computation is segmented and distributed to individual RRHs. Each RRH independently computes its own precoding matrix based on local channel state information, eliminating the need to transmit full channel feedback from all RRHs to the base station controller. This segmentation reduces communication overhead while maintaining interference cancellation capability through coordinated precoding.
Solution Approach 2:
Each RRH performs self-service by autonomously computing its precoding matrix using locally available channel estimates. The RRHs do not require centralized computation or exchange of detailed channel information with the base station controller, as each unit independently determines the precoding needed to cancel interference from other RRHs, thereby eliminating prohibitive communication overhead.
2Reliability
If channel feedback from all RRHs is transmitted to the base station controller, then centralized precoding can be computed, but the communication overhead scales prohibitively with massive MIMO architectures
Solution Approach 1:
The system transitions from centralized precoding requiring global channel information to distributed precoding where each RRH uses only its local channel state information to compute precoding. This local quality approach ensures that each RRH has the necessary information for accurate precoding without requiring transmission of large volumes of channel feedback data across the network.
3Loss of information
If distributed computation is implemented at each RRH, then communication overhead is reduced, but coordination between RRHs for inter-RRH interference precoding becomes necessary
Solution Approach 1:
The base station controller performs preliminary action by providing each RRH with channel state information from other RRHs in advance. This preliminary provision of information enables each RRH to compute its precoding matrix locally without requiring real-time coordination or exchange of data with other RRHs, thereby reducing communication overhead while managing computation complexity through pre-processing.
Data Source
AI summary
A method and apparatus for performing distributed computation of precoding estimates within a DAS. An RRH comprises a receiver component arranged to receive uplink signals from active user devices. The RRH further comprises a processing component arranged to perform channel estimation for each active user device m, based on the received uplink signals, to obtain channel estimates Hm,i between each active user device m and the RRH, compute intra-RRH interference precoding estimates Fm for each active user device m based on the channel estimates Hm,i, and solve interference-free conditions to obtain inter-RRH interference precoding estimates for each RRH j within the DAS.