Online MIMO Precoding for Virtualized Wireless Networks
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Solution Overview
Problem
Current MIMO wireless network virtualization systems face challenges in optimizing downlink precoding under unknown channel information and inaccurate CSI, leading to interference and inefficient resource allocation, particularly in scenarios with long-term and short-term power constraints.
Innovation Solution
An online MIMO WNV method is developed, employing a semi-closed form water-filling-like precoding solution that minimizes the expected deviation of received signals between virtual and actual precoding, using a drift-plus-penalty technique for stochastic network optimization, which operates without requiring channel distribution information and accommodates both short-term and long-term power constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If Service Providers independently design precoding matrices without knowing other SPs' actions, then each SP can simplify its design process and operate autonomously, but inter-SP interference increases and system performance deteriorates
Solution Approach 1:
The Infrastructure Provider acts as an intermediary that collects precoding matrices from multiple Service Providers and coordinates them to reduce interference. The InP processes the virtual precoding matrices from SPs and generates coordinated actual precoding matrices that account for inter-SP interference, enabling autonomous SP operation while maintaining system-wide performance
Solution Approach 2:
The system separates the precoding design into two independent layers: virtual precoding matrices designed independently by each SP for their own users, and actual precoding matrices coordinated by the InP to manage inter-SP interference. This segmentation allows SP autonomy while enabling centralized interference management
2Reliability
If the InP coordinates precoding matrices to reduce inter-SP interference, then system performance and signal quality improve, but the complexity of the InP's processing increases
Solution Approach 1:
Service Providers generate virtual precoding matrices that represent their desired signal directions and power allocations. The InP receives these virtual precoding matrices as inputs and uses them to compute the actual precoding matrices. This copying approach allows the InP to leverage SPs' local optimizations while adding coordination to reduce interference
Solution Approach 2:
The InP transforms the virtual precoding matrices from SPs into actual precoding matrices by adjusting parameters to account for inter-SP interference. This parameter transformation enables the system to maintain the beneficial properties of independent SP design while incorporating interference coordination
3Manufacturing precision
If the system uses offline optimization approaches with known channel distribution information, then optimal precoding can be achieved, but the system cannot adapt to unpredictable channel variations and requires accurate CDI
Solution Approach 1:
The system transitions from static offline optimization to dynamic online optimization where the InP continuously updates the actual precoding matrices based on current channel state information and power constraints. This dynamic approach allows the system to adapt to unpredictable channel variations while maintaining optimization performance
Solution Approach 2:
The online optimization algorithm uses only the observed channel statistics and power constraints to generate precoding matrices without requiring external channel distribution information. The system serves itself by learning from observed channel behavior rather than relying on pre-characterized channel models
4Object-generated harmful factors
If the InP enforces strict physical resource isolation by allocating exclusive sub-carriers and antennas to SPs, then interference between SPs is eliminated, but resource utilization efficiency decreases
Solution Approach 1:
Multiple Service Providers share the same physical resources (antennas and spectrum) of the InP simultaneously. The InP coordinates the precoding matrices of multiple SPs to serve different user groups using the same physical infrastructure, merging resource usage while maintaining service isolation through precoding coordination
Data Source
AI summary
A method, system and apparatus are disclosed. According to one aspect, a network node configured to communicate with a wireless device (WD), includes processing circuitry configured to perform downlink wireless network virtualization by minimizing an expected deviation of received signals at WDs subject to network node power constraints.