Software-Defined Distributed Antenna Reconfiguration for Load Balancing
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Solution Overview
Problem
Existing Distributed Antenna Systems (DAS) face challenges in managing varying subscriber loads, optimizing radio resource usage, and achieving indoor location accuracy, leading to inefficiencies and high costs, particularly in dynamic environments like enterprise facilities.
Innovation Solution
A Reconfigurable Distributed Antenna System employing software-defined radio technology with frequency-selective Digital Up-Converters and Down-Converters, integrated Pilot Beacons, and a software-programmable Remote Radio Head architecture for flexible simulcast, automatic traffic load-balancing, and enhanced location accuracy, allowing dynamic reconfiguration and efficient use of optical fiber bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If many low-power high-capacity base stations are deployed throughout the facility to accommodate maximum subscriber loading, then quality of service is improved, but total life cycle cost increases due to wasted capacity during low-usage periods
Solution Approach 1:
The patent implements dynamic reconfiguration of DAS remote units through software control, allowing the system to adapt radio resource allocation to real-time subscriber loading conditions. The controller dynamically adjusts which remote units are active and how radio resources are distributed, transforming the static base station deployment into a dynamic system that optimizes capacity utilization based on actual demand patterns throughout the day.
Solution Approach 2:
The system changes operational parameters of the DAS by remotely reconfiguring remote units through software commands. The controller modifies parameters such as radio resource allocation, remote unit activation status, and signal transmission characteristics dynamically, allowing the same physical infrastructure to operate at different capacity levels matching actual subscriber needs rather than fixed maximum capacity.
2Ease of manufacture
If a fixed DAS configuration is deployed during the design process, then initial setup is simplified, but the system requires frequent manual reconfiguration when enterprise re-organizations occur, increasing operational complexity
Solution Approach 1:
The system enables self-service reconfiguration by automatically detecting changes in subscriber loading patterns and enterprise usage patterns, then autonomously reconfiguring remote unit assignments and radio resource allocation through software control. The controller monitors network traffic and subscriber distributions, and automatically adjusts the DAS configuration without requiring manual intervention from IT staff, allowing the system to adapt to enterprise re-organizations dynamically.
Solution Approach 2:
The patent transforms the static fixed DAS configuration into a dynamic system that can be remotely reconfigured through software. The controller enables real-time or near-real-time adjustments to remote unit assignments, radio resource allocation, and system parameters, allowing the DAS to adapt flexibly to changing enterprise structures and usage patterns without physical redeployment or complex manual reconfiguration procedures.
3Adaptability or versatility
If manual monitoring and adjustment of DAS remote unit configuration is performed by enterprise IT manager, then some level of adaptability is achieved, but the inability to accurately determine loading at each remote unit leads to suboptimal configuration
Solution Approach 1:
The system implements automated feedback mechanisms where the controller continuously monitors subscriber loading, traffic patterns, and usage statistics at each remote unit and other network elements. This feedback information is used to automatically adjust remote unit configurations, radio resource allocation, and system parameters, replacing manual guessing with data-driven automated decision-making that precisely matches configuration to actual loading conditions at each location.
Solution Approach 2:
The DAS system performs self-optimization by automatically measuring loading conditions at each remote unit through embedded monitoring capabilities and autonomously adjusting its configuration based on these measurements. The controller executes algorithms that analyze traffic patterns, subscriber distributions, and usage statistics to dynamically reconfigure the system, eliminating the need for manual monitoring while achieving precise, data-driven optimization that adapts to changing conditions in real-time.
4Reliability
If base stations are provisioned with enough radio resources to accommodate maximum subscriber loading, then capacity requirements are met during peak times, but cost per subscriber increases due to underutilization during low-usage periods
Solution Approach 1:
The patent implements dynamic radio resource allocation within the DAS, where the controller continuously adjusts the amount of radio resources assigned to each remote unit based on real-time subscriber loading and traffic demand. During peak periods, maximum capacity is available; during low-usage periods, radio resources are automatically reduced or reallocated, allowing the system to maintain capacity availability when needed while minimizing resource consumption and associated costs during periods of low demand.
Solution Approach 2:
The system dynamically changes radio resource parameters such as bandwidth allocation, power levels, and remote unit activation status based on measured loading conditions. The controller adjusts these parameters in response to traffic patterns and subscriber distributions, enabling the DAS to provision radio resources flexibly - providing full capacity during peak times while reducing resource allocation during low-usage periods to optimize cost efficiency.
Data Source
AI summary
The present disclosure is a novel utility of a software defined radio (SDR) based Distributed Antenna System (DAS) that is field reconfigurable and support multi-modulation schemes (modulation-independent), multi-carriers, multi-frequency bands and multi-channels. The present disclosure enables a high degree of flexibility to manage, control, enhance, facilitate the usage and performance of a distributed wireless network such as flexible simulcast, automatic traffic load-balancing, network and radio resource optimization, network calibration, autonomous/assisted commissioning, carrier pooling, automatic frequency selection, frequency carrier placement, traffic monitoring, traffic tagging, pilot beacon, etc.