Operational Area Planning of a Generic Cellular Network
This application provides comprehensive capacity, cost, and performance analysis, alongside resource allocation planning for cellular communication networks employing dedicated logical communication channels. By supporting TDMA, FDMA, CDMA, and hybrid multiple-access technologies, the framework enables engineers to evaluate network coverage, channel allocation, and quality of service prior to deployment.
Problem Definition
The primary objective is to maximize cellular network coverage while minimizing the probability of connection blocking across the operational area. To achieve this, cell placement and resource allocations are optimized based on a spatial traffic density (temperature) map representing localized call initiation probabilities, subject to specified deployment conditions.
Temperature Data
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The operational area is represented by a grayscale bitmap where each pixel provides a point of measured or interpolated connection probability data, with darker pixels indicating a lower probability of connection attempts. Higher resolution images yield more accurate results, and this underlying temperature data can be generated using measurement statistics provided by operators or third parties.
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Temperature Points
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Before deployment begins, all temperature points are sorted according to their traffic intensity. Temperature points are pre-processed and ordered. The planner can operate using one of two deployment strategies:
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Cell Deployment
Cells are deployed iteratively by adding new cell centers to yet uncovered temperature points. Each newly deployed base station is assigned the largest allowable coverage radius (power level) that does not overlap the center locations of previously existing cells.
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| Initial Cell Deployment | Deploying Additional Cells and Updating BSC/CNS | Progressive Network Expansion | Complete Operational Coverage |
Channel and Coverage Assignment
Each cell is initially assigned the minimum allowable number of communication channels—defined as the number of users that can simultaneously receive service—alongside the maximum permissible coverage radius. Both parameters are fully configurable within the simulation properties.
The planner continuously evaluates the traffic load within every deployed cell against an allowable threshold. Specifically, it computes the ratio of the total temperature values within the cell over its current channel count. If this value exceeds the threshold ratio—defined as the highest possible total temperature of a cell with minimum radius over the maximum allowed channels—the system initiates a step-by-step optimization loop:
- Channel Scale-Up: Additional channel bundles are dynamically assigned one bunch at a time, re-evaluating the cell at each step until maximum channel capacity is reached.
- Radius Reduction: If maximum channel capacity has already been allocated and the threshold is still exceeded, the coverage radius is gradually decreased one level at a time to shed traffic load, down until the minimum allowable radius is met.
Computational Scaling Requirements
| Parameter | Value |
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| Operational Area | 25 × 25 km² |
| Cell Radius | 3 – 9 km |
| Channels per Cell | 10 – 250 (5 channels per bundle) |
| User Density | 0.0001 – 0.0004 users/m² |
| Users (25 × 25 km²) | 62,500 – 250,000 |
| Users (100 × 100 km²) | 1,000,000 – 4,000,000 |
| Connection Duration | 2 seconds – 2 minutes |
| Idle Duration | 10 seconds – 3 hours |
| Simulation Duration | 3 hours |
| Simulation Step | 1 second |
| Random Solutions Evaluated | 1,000 |
User Deployment
After the cellular infrastructure is deployed, a predefined number of user equipments (UEs) are generated and distributed across the operational area.
Each user is initially assigned to one of the serving cells covering its location. During the simulation runtime, a user equipment may change its serving cell and reassign to a neighboring cell if no available communication channels are left. If no alternative cell can accommodate the connection request, the blocked-attempts counter is incremented by 1.
Simulation Execution
As soon as cells and user equipments are deployed on the operational area, the discrete-event simulation can be started.
Temperature-Based Cellular Planning Algorithm
All users attempt to establish a connection according to a uniformly distributed random process. The probability of initiating a call is a uniform random number bounded between 0.0 and the temperature value of that specific coordinate pixel; for instance, a half-bright pixel yields a connection probability of 0.5. Consequently, brighter pixels generate significantly more connection attempts than darker regions.
Call durations and idle time periods are generated independently using uniform random distributions.
The principal performance metric is the Probability of Connection Blocking, defined as the frequency probability ratio of unsuccessful connection attempts over all attempted connections.
Random Cell Deployment
For comparison and baseline evaluation, this process is utilized to generate random cellular infrastructure layouts across the operational area.
Alternative Solution Generation Algorithm
Similar to the main algorithm, cell positions are based on the pre-processed and ordered temperature points. However, the coverage radius (power level) is randomly assigned within allowed boundaries ensuring it does not cover existing cell centers, and the initial channel count is also randomly generated within predefined operational limits.
Random Solutions (1000 Trials)
The distribution of connection blocking probabilities obtained from 1,000 randomly generated network coverage and deployment plans.
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Results
Best random deployment solutions compared with the least favorable
temperature-based planning solution in terms of connection blocking probability.
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Conclusion
Temperature-based cellular network planning allocates cells and communication channels efficiently according to spatial traffic demand, deploying resources directly to high-traffic areas and resulting in significantly improved utilization of network infrastructure.
For dense operational scenarios containing between 100,000 and 200,000 users, the proposed methodology achieves connection blocking probabilities as low as 5% to 10% of those observed in heavily over-provisioned, manually designed networks.
By enabling more effective cell and channel allocation, this optimization framework obtains superior resource utilization and reduced deployment costs while maintaining high quality of service—even when comparing the worst temperature-based planning outcomes against the best randomly generated solutions.
Best Random Planning Solutions
| Number of Cells vs. User Count | Number of Channels vs. User Count |
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