Operational Area Planning of a Generic Cellular Network

This application provides capacity planning, performance evaluation, and resource allocation for cellular communication networks employing dedicated logical communication channels. The framework supports TDMA, FDMA, CDMA, and hybrid multiple-access technologies, enabling engineers to evaluate network coverage, channel allocation, and quality of service before deployment.

Problem Definition

The objective is to maximize cellular coverage while minimizing the probability of connection blocking. Cell placement is optimized using a spatial traffic density (temperature) map that represents the probability of call initiation throughout the operational area.

Temperature Map

The operational area is represented by a grayscale bitmap, where pixel intensity corresponds to the probability of call initiation. Darker pixels represent lower traffic demand. Brighter pixels represent higher traffic demand. Higher image resolution produces more accurate deployment results. Each pixel represents either measured or interpolated traffic statistics. The traffic map can be generated from operator measurements or third-party datasets.

Temperature Point Ordering

Before deployment begins, all temperature points are sorted according to their traffic intensity. The planner can operate using one of two deployment strategies: Hottest Point First — prioritizes high-demand regions, resulting in more cells, higher reliability, and increased deployment cost. Coldest Point First — prioritizes low-demand regions, resulting in fewer cells, reduced deployment cost, and lower overall reliability.

Cell Deployment

Cells are deployed iteratively by selecting uncovered temperature points. Each new base station is assigned the largest allowable coverage radius that does not overlap the center locations of previously deployed cells.

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 together with the maximum permissible coverage radius. Both parameters are configurable.

The planner continuously evaluates traffic load within every deployed cell.

• If the traffic-to-channel ratio exceeds the allowable threshold, additional channel bundles are assigned until the maximum channel capacity is reached.
• If the maximum channel capacity has already been allocated, the coverage radius is gradually reduced to decrease the served traffic load until the minimum allowable radius is reached.

Computational Scaling Requirements

Parameter	Value
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 has been generated, the specified number of user equipments (UEs) are randomly distributed across the operational area.

Each user is initially associated with the serving cell covering its location. During the simulation, users may be reassigned to neighboring cells whenever channel resources become unavailable. If no suitable cell can accommodate a connection request, the blocked-attempt counter is incremented.

Simulation Execution

Once both infrastructure and users have been deployed, the discrete-event simulation begins.

Temperature-Based Cellular Planning Algorithm

Each user attempts to establish a connection according to a uniformly distributed random process. The probability of initiating a call is bounded by the temperature value of the corresponding map pixel. Consequently, brighter pixels generate more connection attempts than darker regions.

Connection durations and idle periods are generated independently using uniform random distributions.

The principal performance metric is the Probability of Connection Blocking, defined as the ratio of unsuccessful connection attempts to the total number of attempted connections.

Random Cell Deployment

For comparison purposes, the framework also generates random deployment solutions. Cell locations follow the ordered temperature map, while coverage radius and channel capacity are selected randomly within predefined operational constraints.

Alternative Solution Generation Algorithm

Random Solutions (1,000 Trials)

Distribution of connection blocking probabilities obtained from one thousand randomly generated network deployment plans.

Results

Best random deployment solutions compared with the least favorable temperature-based planning solution in terms of connection blocking probability.

Conclusion

Temperature-based cellular network planning allocates both cells and communication channels according to spatial traffic demand, resulting in significantly improved utilization of network resources.

For dense operational scenarios containing between 100,000 and 200,000 users, the proposed algorithm achieves connection blocking probabilities as low as 5–10% of those observed in heavily over-provisioned manually designed networks.

The methodology enables more efficient channel allocation, improved network utilization, and reduced deployment cost while maintaining high service quality.

Best Random Planning Solutions

Number of Cells vs. User Count	Number of Channels vs. User Count