Adaptive Spectrum Allocation for Wireless Capacity Optimization
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Solution Overview
Problem
The existing spectrum allocation methods in wireless communications are inefficient, requiring manual and time-consuming processes for exclusive licensed spectrum, and face challenges with limited available spectrum and interference issues, especially with the growing demand for wireless communications.
Innovation Solution
The technology dynamically allocates spectrum by utilizing a Spectrum-as-a-Service model, allowing for on-demand access and reallocation of CBRS spectrum, adjusting the uplink-to-downlink ratio, and relocating hotspots to optimize wireless capacity based on demand, leveraging a radio access network intelligent controller and application programs for adaptive management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual spectrum allocation processes are used for exclusive licensed spectrum, then spectrum can be allocated to users, but the process takes much time and is not automated
Solution Approach 1:
The system enables self-service through automated spectrum allocation where the spectrum access system and network controller automatically allocate and manage spectrum resources without manual intervention. The system monitors spectrum usage, detects available bands, and allocates spectrum to users autonomously based on predefined policies and real-time conditions.
Solution Approach 2:
The system performs preliminary actions by pre-configuring spectrum allocation policies, user authorization levels, and interference management rules before actual spectrum allocation occurs. This preparation enables rapid automated decision-making when spectrum allocation is needed, eliminating manual configuration time.
2Productivity
If more spectrum is allocated to meet growing wireless demand, then wireless capacity increases, but interference becomes more problematic
Solution Approach 1:
The system applies local quality by allocating spectrum resources specifically to geographic locations and user groups where they are most needed, rather than uniform allocation. It identifies specific frequency bands suitable for particular areas and users, optimizing capacity while minimizing interference through localized, targeted spectrum assignment.
Solution Approach 2:
The system implements continuous feedback mechanisms by monitoring spectrum usage, interference levels, and network performance in real-time. Based on this feedback, the spectrum access system dynamically adjusts allocation decisions, reconfigures spectrum assignments, and modifies transmission parameters to maintain high capacity while minimizing interference through adaptive control.
3Adaptability or versatility
If CBRS spectrum sharing is implemented to manage multiple user priorities, then spectrum utilization improves, but system complexity increases
Solution Approach 1:
The system segments spectrum management into distinct functional components: a spectrum access system for high-level policy enforcement and coordination, and network controllers for local spectrum allocation decisions. This segmentation distributes complexity across multiple manageable entities, enabling sophisticated CBRS spectrum sharing with incumbent, priority, and general authorized access users through modular architecture.
4Productivity
If dynamic spectrum allocation is implemented to optimize wireless capacity, then spectral efficiency improves, but control and measurement complexity increases
Solution Approach 1:
The system introduces intermediary components including spectrum sensors that detect available spectrum and interference conditions, and the spectrum access system that mediates between detection data and allocation decisions. These intermediaries simplify the control and measurement process by handling the complexity of real-time spectrum monitoring and translating it into actionable allocation decisions that optimize spectral efficiency.
Data Source
AI summary
The described technology is generally directed towards adaptive spectrum as a service, in which spectrum can be dynamically allocated to adapt to demand for wireless capacity. The demand for wireless capacity can be based on monitoring system state, and/or proactively predicted based on other system state such as time of day. Reallocated spectrum can be monitored for performance, to converge spectrum allocation to a more optimal state. Allocated spectrum can be relocated, increased or decreased, including by the use of citizens band radio service spectrum or other spectrum. Currently allocated spectrum can be adapted into modified allocated spectrum by an application program (xApp) coupled to a radio access network intelligent controller (RIC), a citizens broadband radio service device, a domain proxy service, and/or a user device.