MU-MIMO-OFDM Resource Allocation via Capacity Proportional Power
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Solution Overview
Problem
Current resource allocation methods for MU-MIMO-OFDM systems fail to effectively address the issue of link outage due to path loss and channel fading, leading to suboptimal signal-to-noise ratio and capacity constraints, especially in multi-user environments with varying data transmission sizes.
Innovation Solution
A resource allocation method that assigns preset sub-channel numbers to users based on capacity ratio constraints, using scheduling rules like Max-Min and Max Sum-Rate to optimize sub-channel allocation, ensuring each user selects sub-channels that maximize link quality and meet data size requirements, thereby enhancing coverage and capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If power is divided among multiple antennas in MIMO system, then transmission rate is enhanced, but covering range becomes smaller compared to SISO system
Solution Approach 1:
The patent changes the allocation parameters from equal power distribution to capacity-proportional power distribution. By dynamically adjusting the power allocation ratio based on each user's channel capacity, the system achieves both high transmission rates for users with good channels and adequate coverage for users with poor channels, resolving the contradiction between transmission rate enhancement and covering range reduction.
2Reliability
If scheduling algorithm enhances signal strength of weakest antenna, then soft coverage enhancement is achieved, but additional transmit power is required
Solution Approach 1:
The patent implements a self-service mechanism where users with better channel conditions automatically provide power to the system through their higher capacity channels. The power allocation algorithm leverages the natural channel diversity, allowing strong channels to carry more power and indirectly support weaker channels through efficient resource utilization, achieving coverage enhancement without additional hardware power.
3Device complexity
If sub-channel allocation does not consider capacity ratio constraints, then allocation complexity is reduced, but link outage occurs due to path loss and channel fading
Solution Approach 1:
The patent applies preliminary action by pre-calculating and establishing capacity ratio constraints before sub-channel allocation. These constraints are derived from channel state information and are used to guide the allocation process, ensuring that users with poor channel conditions are assigned sub-channels that maintain their link quality above outage thresholds, while users with good channels receive sub-channels that maximize system capacity.
4Adaptability or versatility
If flexible transmission rate is provided for each user, then user-specific data size requirements are met, but resource allocation becomes more complex
Solution Approach 1:
The patent implements dynamics by making the power allocation ratio adaptive rather than static. The allocation ratio dynamically adjusts based on real-time channel conditions and user capacity ratios, allowing the system to flexibly meet different user data size requirements. This dynamic approach maintains manageable complexity by using closed-form solutions based on channel state information, avoiding the need for complex iterative optimization.
Data Source
AI summary
The present invention is direct to the resource allocation method for MU-MIMO-OFDM system and the apparatus thereof. The MU-MIMO-OFDM system has a plurality of users and a plurality of sub-channels. The sub-channels are assigned to the users according to the capacity ratio constraints and a scheduling rule, and then the power of the user is determined according to the limit power of the MU-MIMO-OFDM system. Wherein the values of power of the sub-channels assigned to the user are the same, the scheduling rule may be Max-Min or Max Sum-Rate rule, and the allocation of the sub-channels may be user-oriented or sub-channel oriented.