DAS Capacity Optimization via Dynamic Attenuation and Traffic Monitoring
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Solution Overview
Problem
Distributed antenna systems face inefficiencies in capacity optimization, as they often provide excessive capacity during low-demand periods, leading to unnecessary energy consumption and potential dropped calls due to rapid capacity redistribution.
Innovation Solution
A capacity optimization sub-system comprising a switch matrix with variable attenuators and switches, and a controller that adjusts capacity among coverage zones based on detected traffic levels, gradually redistributing capacity by attenuating signals to prevent dropped calls and optimize energy use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If capacity is constantly provided at maximum level to ensure coverage for the maximum number of wireless devices, then coverage reliability is improved, but energy consumption increases unnecessarily during low-demand periods
Solution Approach 1:
The system dynamically adjusts capacity allocation based on real-time traffic conditions. The controller continuously monitors traffic levels in each coverage zone and reconfigures the switch matrix and variable attenuators to allocate capacity dynamically, transitioning from static maximum capacity provision to adaptive capacity management that matches actual demand.
Solution Approach 2:
The system changes operational parameters (capacity allocation levels) based on traffic conditions. By monitoring traffic levels and adjusting capacity parameters upward or downward accordingly, the system optimizes the balance between coverage reliability and energy consumption, avoiding the fixed parameter approach of constantly maintaining maximum capacity.
2Productivity
If capacity is rapidly redistributed from coverage zones with excess capacity to zones with high demand, then capacity utilization efficiency is improved, but service reliability deteriorates due to dropped calls
Solution Approach 1:
The system performs preliminary actions by gradually attenuating signals in coverage zones with excess capacity before fully redistributing capacity. This gradual approach gives wireless devices time to detect the capacity reduction and initiate handover procedures to alternative coverage zones, preventing dropped calls during capacity redistribution.
Solution Approach 2:
The system uses feedback mechanisms where the controller monitors traffic levels and capacity allocation in real-time, continuously adjusting the configuration of switch matrix and variable attenuators. This closed-loop control ensures smooth capacity transitions and maintains service reliability by responding to actual system conditions.
Data Source
AI summary
Certain aspects are directed to a capacity optimization sub-system for a distributed antenna system. The capacity optimization sub-system includes a switch matrix and a controller. The switch matrix includes variable attenuators and switches. The switch matrix can receive sectors from base stations. The switch matrix can provide the sectors to coverage zones. The controller can communicate with the switch matrix. The controller can determine that a number of wireless devices in one or more of the coverage zones is outside a specified range of threshold traffic levels. In response to determining that the number of wireless devices is outside the specified range of threshold traffic levels, the controller can configure one or more of the variable attenuators and corresponding switches to redistribute capacity among the coverage zones by, for example, increasing and/or decreasing capacity in one or more of the coverage zones.