Coordinated Precoding Under Per-Antenna Power Constraints
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Solution Overview
Problem
Current linear precoding schemes for MIMO broadcast and interference channels primarily focus on sum power constraints, neglecting per-antenna power constraints, which are more relevant in practical cellular downlink scenarios, leading to inefficiencies in resource allocation and interference management.
Innovation Solution
The method involves initializing and updating transmit precoders, receiver filters, and slack variables using closed-form expressions, iteratively optimizing them under per-antenna power constraints to achieve efficient precoding for multiple stream data transmission across slots in a communication system with multiple transmitters and receivers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If linear precoding schemes are designed under sum power constraint, then the design is simpler and more conventional, but the scheme is less relevant to practical cellular downlink scenarios where per-antenna power constraints apply
Solution Approach 1:
The patent transforms the per-antenna power constraint problem into an equivalent sum power constraint problem by introducing a power allocation matrix that redistributes power across antennas. This parameter transformation allows the system to satisfy practical per-antenna constraints while utilizing conventional sum power constraint design methods, thereby resolving the contradiction between practical relevance and design simplicity
Solution Approach 2:
The patent introduces an intermediary power allocation matrix that acts as a mediator between the per-antenna power constraints and the precoding design. This matrix transforms the original constrained optimization problem into an unconstrained equivalent, allowing standard precoding techniques to be applied while still enforcing per-antenna power limits through the intermediary transformation
2Productivity
If per-antenna power constraints are enforced, then resource allocation efficiency is improved, but the optimization problem becomes more complex and computationally intensive
Solution Approach 1:
The patent changes the parameter representation by introducing a power allocation matrix that converts per-antenna power constraints into an equivalent sum power constraint formulation. This parameter transformation reduces computational complexity while maintaining resource allocation efficiency, as it allows the use of simpler optimization algorithms on the transformed problem
3Reliability
If iterative updates of transmit precoders, receiver filters, and slack variables are performed, then weighted-sum rate optimization is enhanced, but the computational burden and convergence time increase
Solution Approach 1:
The patent performs preliminary actions by initializing the power allocation matrix and transforming the constraint structure before the main iterative optimization process. This preliminary transformation simplifies subsequent iterations by converting a complex constrained problem into a simpler equivalent form, reducing the computational burden per iteration and potentially加快ing convergence
Solution Approach 2:
The patent segments the optimization problem into distinct components: power allocation matrix optimization, transmit precoder optimization, and receiver filter optimization. This segmentation allows each component to be optimized separately in an iterative manner, making the overall complex problem more tractable and enabling parallel computation of different segments
Data Source
AI summary
There is provided a method for generating transmit precoders for a communication system having a plurality of transmitters and a plurality of receivers forming a plurality of transmitter-receiver pairs. Each of the transmitters and receivers has a respective plurality of antennas. The method includes initializing the transmit precoders. The method further includes updating a plurality of receiver filters and a plurality of slack variables using closed form expressions. The method also includes updating the transmit precoders responsive to an output of said prior updating step. The method additionally includes iteratively repeating the updating steps until convergence is reached to obtain a final set of transmit precoders. The transmit precoders are updated to perform precoding for multiple stream data transmission for each of the plurality of transmitter-receiver pairs on each of a plurality of slots under a per-antenna power constraint imposed on each of the plurality of antennas.