HSDPA Radio Network Planning with Monte Carlo Sub-Snapshot Analysis
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Solution Overview
Problem
Current HSDPA analysis tools in radio network planning fail to accurately account for multiple users in a cell, channel-dependent scheduler effects, and fast fading, leading to discrepancies in performance prediction and actual network performance, especially in high-density scenarios.
Innovation Solution
A system and method that utilize a Monte Carlo analysis module with sub-snapshot generation and evaluation, incorporating scheduling and resource requirement calculations to efficiently simulate HSDPA performance, reducing computational complexity and improving accuracy by accounting for multiple users and dynamic resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dynamic simulation is used for HSDPA connections to study fast fading and scheduler effects, then measurement precision is improved, but device complexity increases and productivity decreases due to large CPU time requirements
Solution Approach 1:
The patent segments the simulation process into two distinct parts: a Monte Carlo simulator for UMTS connections and a dynamic simulator for HSDPA connections. This segmentation allows each simulator to be optimized for its specific purpose, with the Monte Carlo simulator handling general network planning and the dynamic simulator focusing specifically on HSDPA performance analysis, thereby improving overall efficiency while maintaining accuracy
Solution Approach 2:
The patent applies partial action by using the dynamic simulator only for HSDPA connections rather than for all network simulations. This selective application of computationally intensive dynamic simulation only where needed (for HSDPA) while using faster Monte Carlo methods for other scenarios reduces overall CPU time requirements while still capturing the essential fast fading and scheduler effects for HSDPA
2Productivity
If Monte Carlo simulators are used for network planning, then productivity is improved through faster analysis, but measurement precision deteriorates by not accounting for fast fading and scheduler effects
Solution Approach 1:
The patent divides the simulation capability into two segments: Monte Carlo simulation for general UMTS network planning and dynamic simulation specifically for HSDPA connections. This allows operators to use the fast Monte Carlo method for overall network planning while applying the more accurate dynamic simulation only when HSDPA performance analysis is required
Solution Approach 2:
The patent creates a universal planning system that can handle both traditional UMTS connections and HSDPA connections through a single integrated tool. The system automatically selects the appropriate simulation method (Monte Carlo or dynamic) based on the connection type, providing both speed and accuracy across different scenarios
3Power
If available transmission power is not reduced for HSDPA connections, then HSDPA throughput is improved, but harmful factors increase due to radio interference affecting overall network performance
Solution Approach 1:
The patent implements feedback mechanisms where the dynamic simulator monitors the impact of HSDPA transmissions on overall network performance and adjusts power allocation accordingly. The scheduler uses feedback about interference levels and channel conditions to dynamically adjust transmission parameters, ensuring that HSDPA connections receive sufficient power while maintaining acceptable interference levels for other users
Solution Approach 2:
The patent introduces dynamic power adjustment where transmission power is not fixed but adapts based on real-time channel conditions, interference levels, and network load. The channel-aware scheduler dynamically modifies transmission parameters including power allocation to optimize HSDPA performance while controlling interference, rather than using static power levels
Data Source
AI summary
A system and method for radio network planning comprises a grid generator and a Monte Carlo analysis module. The Monte Carlo analysis module comprises a snapshot generation module which draws, for each snapshot and for each pixel, a statistical realization from a distribution function relating to slow fading, and a snapshot evaluation module which establishes radio network parameters. The Monte Carlo analysis module further comprises a sub-snapshot generation module which generates at least one sub-snapshot for each evaluated snapshot result, and a sub-snapshot evaluation module (14) for evaluating HSDPA performance parameters based on the sub-snapshot. The sub-snapshot evaluation module (14) comprises a scheduler module (16) which is arranged for scheduling a HSDPA user according to a scheduling scheme.