<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Frequency planning is one of the most expensive aspects of deploying a cellular network. If a set of base stations can be deployed with minimal service and planning, the cost of both deploying and maintaining the network will decrease. To ensure that the scarce frequency is utilized to its maximum, planning and optimization are done. This is also carried out to ensure that there is high efficiency in cellular radio systems and little or minimum interference due to co-channeling. This paper focuses on coming up with an automatic way of planning and optimizing the frequency in the cellular network. The approach replaces the inefficient, inaccurate and tedious manual approach. The automatic approach simplifies work for the radio frequency(RF) engineers and also reduces the cost of operation. The automatic approach ensures that the cellular network is extensively deployed in a way that criteria of maximum quality, quantity and good coverage are met. The paper focuses on coming up with an automatic planning and optimization algorithm that minimizes the intra-system interference levels to reasonable ranges within the key performance indicators (KPIs) defined for any acceptable cellular network.</p>
</abstract>

Frequency planning is one of the most expensive aspects of deploying a cellular network. If a set of base stations can be deployed with minimal service and planning, the cost of both deploying and maintaining the network will decrease. To ensure that the scarce frequency is utilized to its maximum, planning and optimization are done. This is also carried out to ensure that there is high efficiency in cellular radio systems and little or minimum interference due to co-channeling. This paper focuses on coming up with an automatic way of planning and optimizing the frequency in the cellular network. The approach replaces the inefficient, inaccurate and tedious manual approach. The automatic approach simplifies work for the radio frequency(RF) engineers and also reduces the cost of operation. The automatic approach ensures that the cellular network is extensively deployed in a way that criteria of maximum quality, quantity and good coverage are met. The paper focuses on coming up with an automatic planning and optimization algorithm that minimizes the intra-system interference levels to reasonable ranges within the key performance indicators (KPIs) defined for any acceptable cellular network.

Performance of Automatic Frequency Planning and Optimization Algorithm for Cellular Networks

International Journal of Advanced Network, Monitoring and Controls

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Frequency planning is one of the most expensive aspects of deploying a cellular network. If a set of base stations can be deployed with minimal service and...

Calls Arriving in B3 (SumnB3)	Sum of borrowed Channels (n)	Sum of blocked calls in DCA (Sumnb)	Sinn of blocked in FCA (Sumnb1)	Probability of call block m DCA	Probability of call block in FCA	% Blocked calls in DCA	% Blocked calls in FCA
812	6	16	302	0.0197	0.372	1.97	37.2
753	6	12	260	0.0159	0.345	1.59	34.5
764	1	22	285	0.0289	0.373	2.89	37.3
734	5	34	272	0.0463	0.371	4.63	37.1
784	3	13	274	0.0166	0.349	1.66	34.9
739	5	18	246	0.0244	0.333	2.44	33.3
704	5	19	250	0.0270	0.355	2.70	35.5
721	5	14	226	0.0194	0.313	1.94	31.3
817	5	22	312	0.0269	0.382	2.69	38.2
697	4	22	229	0.0316	0.329	3.16	32.9
777	5	0	289	0	0.372	0	37.2
826	2	8	302	0.097	0.366	0.97	36.6
785	5	12	289	0.0153	0.368	1.53	36.8
823	3	13	306	0.0158	0.372	1.58	37.2
682	2	16	223	0.0235	0.327	2.35	32.7
791	9	44	282	0.056	0.357	5.56	35.7
713	5	10	263	0.0140	0.369	1.40	36.9

Channel Groups	A1	B1	C1	A2	B2	C2	A3	B3	C3
RF Channels	1	2	3	4	5	6	7	8	9
	10	11	12	13	14	15	16	17	18
	19	20	21	22	23	24	25

	Deviations
Cell Sites	1	2	3	4	5	6	7	8	9
1	0	1	0.5	0	0.25	0	0	1	0.25
2	0.25	0	0	1	0.75	1	0	0	0
3	0.75	0	0.5	0	0	0	1	−1.074	0.75

Performance of Automatic Frequency Planning and Optimization Algorithm for Cellular Networks

Publicado en línea: 16 ago 2023

Páginas: 54 - 60

DOI: https://doi.org/10.2478/ijanmc-2023-0056

Palabras clave
Automatic Frequency Planning, Optimization Algorithm, Cellular Networks

© 2023 Mohanad Abdulhamid et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Figure 2.

Figure 3.

Cell site geographical location

Matlab simulation results

3/9 Reuse Pattern

AMPL Results

Cell Site #	X Coordinate value (in km)	Y Coordinate value (in km)
1	1	1
2	3	1
3	5	1
4	1	3
5	3	3
6	5	3
7	1	5
8	3	5
9	5	5

Performance of Automatic Frequency Planning and Optimization Algorithm for Cellular Networks

Publicado en línea: 16 ago 2023

Páginas: 54 - 60

DOI: https://doi.org/10.2478/ijanmc-2023-0056

Palabras claveAutomatic Frequency Planning, Optimization Algorithm, Cellular Networks

© 2023 Mohanad Abdulhamid et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Figure 2.

Figure 3.

Cell site geographical location

Matlab simulation results

3/9 Reuse Pattern

AMPL Results

Palabras clave
Automatic Frequency Planning, Optimization Algorithm, Cellular Networks