sfh plan for gsm900

Design Paper: Advanced Frequency Planning Techniques

Alcatel File Reference Date Edition Page 3DC 21150 0345 TQZZA 10/2006 Ed 01 1 All rights reserved. Passing on and copying of this document, use and communication of its contents not permitted without written authorisation.

Advanced Frequency Planning Techniques in

GSM/GPRS/EDGE 1. INTRODUCTION Frequency band is a scarce resource and thus its use needs to be optimized. It is particularly relevant e.g. for operators having limited spectrum but a fast growing subscriber base or for operators contemplating to introduce UMTS in a GSM frequency band. Concretely operators thriving for the best spectrum efficiency would:

- either try and serve as many subscribers as possible with an acceptable quality of service and the lowest amount of spectrum,

- or increase the quality of service for a given number of subscribers and a given spectrum.

Alcatel offers a rich portfolio of best-in-class products and features to improve spectrum efficiency. In addition, Alcatel has developed over the years a strong expertise in advanced frequency planning methods, aiming at maximum spectrum efficiency. This paper is focused on such advanced techniques, which mainly rely on Discrete Frequency Hopping (DFH) and Radio Measurement Statistics (RMS).

2. THE DISCRETE FREQUENCY HOPPING SOLUTION A well-known method for improving radio quality is the “frequency hopping” (FH) feature. This feature aims at taking full benefit of frequency and interference diversities. This is achieved by hopping on different frequencies from one burst to the next, which results in:

- averaging out interference (“collisions”, i.e. two users in nearby cells using the same frequency, are not continuous like may be the case in case of no hopping);

Co-channel interferers (I) Wanted signal (C) Background noise (N)



- averaging out fast fading, especially for slowly moving users. Channel decoding is used to correct errors; because frequency hopping spreads out errors over several bursts, entire information blocks may be recovered, which is less the case without hopping. Two traditional Frequency Hopping techniques exist: Base Band Hopping (BBH) and Synthesized Frequency hopping (SFH).

2.1 Baseband Hopping and Synthesized Frequency Hopping To correctly work, the network needs very good radio conditions on BCCH frequencies. As a consequence, the BCCH frequency band is always planned apart from the TCH frequency band. In particular, BCCH frequencies are not hopping (at least the timeslot carrying the BCCH) and less reused than TCH frequencies in order to ensure the highest quality. Let us now focus on the TCH planning:

• In Baseband hopping, each timeslot is hopping on a number of frequencies that equals the numbers of TRXs in the cell. In this case, the problem is the one of appropriate frequency assignment for each cell, taking into account interfering neighbors.

• In Synthesized Frequency hopping, each timeslot hops on more frequencies than the number of TRXs. More precisely, a “cluster” size is defined (1 for 1 x 1 fractional reuse and 3 for 1 x 3 fractional reuse) and the whole “TCH frequency spectrum” is allocated to each cluster of cells. This approach is simpler than the previous one since it requires less complicated frequency allocation computations (the only issues are the choice of the TCH and BCCH pool sizes and the allocation of BCCH frequencies), while taking full advantage of diversity.

In the Alcatel Base Station, both Baseband hopping and Synthesized Frequency Hopping are managed by a single TRX board, by synthesizing the needed frequencies and modulations on a per timeslot basis.

2.2 Discrete Frequency Hopping Depending on the network’s configuration, one solution may be better than the other: SFH gives priority to diversity whereas BBH is more focused on “intelligent” frequency planning. The idea of discrete frequency hopping (DFH) is to add flexibility by tuning the number of hopping frequencies per cell according to each cell’s number of TRXs and interfering environment. More precisely, appropriate DFH frequency planning is a trade-off between two aspects:

• High frequency and interference diversity thanks to a high number of hopping frequencies per cell • Low interference probability thanks to intelligent frequencies distribution across the network

o A too high number of hopping frequencies would bring for sure a high interference and frequency diversity but the counterpart would be a higher amount of collisions with neighbouring cells. Thus, there is an optimum value for each cell.


Alcatel File Reference Date Edition DC 21150 0345 TQZZA 10/2006 Ed 01 3 All rights reserved. Passing on and copying of this document, use and communication of its contents not permitted without written authorisation.

Basically, DFH can be considered as a particular case of Synthesized Frequency Hopping implementation. Each cell will have a different hopping group, and all frequencies of this group are chosen based on a quality criteria (prediction and/or field data). The counterpart of this “customized” approach is that it requires both to choose the frequency pool size for each cell and to allocate the frequencies appropriately. This computation can be performed with the help of a precise and complete” Interference Matrix” that is computed over all cells of the network. Such a data matrix cannot be obtained easily with traditional tools. Thus, it is convenient to perform the frequency plan with the help of the RMS feature. It is important to note that although it is particularly useful for DFH planning, the RMS feature provides also great benefits when performing a BBH or a SFH planning (used only for the BCCH planning in that case).

DFH is a flexible solution that adapts itself to field characteristics. It takes advantage of the “intelligent” frequency planning from BBH and of the high frequency and interference diversity of SFH. It results in an optimal frequency allocation as well as in an optimal number of hopping frequencies depending on the number of TRX. 3. A POWERFUL FREQUENCY PLANNING TOOL: RMS

3.1 The Interference Matrix The prerequisite for any frequency planning process is the knowledge of the collision probability between users located in different cells but using the same frequency. Then, the frequencies are allocated in such a way that the “cost” of these collisions is the lowest. This collision probability can be estimated through the C/I distribution due to neighbouring users using the same frequency. Practically, these C/I values are computed between each neighbouring cells and are then reported in a so-called “Interference Matrix” that will be the input of an optimisation tool. This matrix can be obtained from:

• Analytical models and Monte Carlo Simulations. This solution may be based on a precise field map. Apart from the fact that it is time demanding, this method will not achieve an outstanding accuracy (clutter, heights, physical sites maps and propagation models are only approximations of reality)

• Field measurement campaigns: costly and manpower demanding, they can neither be performed at a whole network’s scale, nor during a statistically relevant duration.

As a consequence, one has to look for an efficient alternative and cost effective way to perform C/I measurements over a network. The answer to this issue is the RMS (Radio Measurement Statistics) feature.



3.2 RMS: Mobile stations are measurement tools Through the RMS feature, Mobile stations are used as measurement tools. Among other things, RMS reports C/I values experienced by mobiles between their serving cell and the neighbouring cells. Indeed, each mobile computes the signal strength of its serving cell’s BCCH frequency and the signal strength of the neighbouring cell’s BCCH frequency. The ratio between both values is an accurate approximation of the effective C/I level.

3.3 The “dummy neighbours” method In addition to the interference measured from neighbour cell’s BCCH, it is possible to perform other measurements so that the Interference Matrix will be more complete (a mobile station can select up to 32 different frequencies). To do this, virtual neighbouring frequencies (“dummy neighbours”) are created at the OMC-R in such a way that the mobile stations perform measurements between their serving cell and these additional frequencies that will correspond to “higher order neighbours” in the network.

???Neighbor cellsOther cells

Serving cell

The main benefits of the RMS feature are to enable automated frequency planning and the building of a precise interference matrix based on field results. This allows optimising network KPIs without the costly use of drive test equipments or Abis traces.

OMC

BSC

BCCH

BCCH

BCCH BCCH

BCCH BCCH



4. APPLICATION: SOME FIELD RESULTS This part presents some results that were observed after a switch from SFH (1 x3) to DFH using RMS feature. As an example, the following table gives the number of hopping frequencies depending on the number of TRX for this DFH implementation. One can notice that DFH behaves like SFH for cells with less than 4 TRXs whereas it behaves like BBH for cells with more than 4 TRXs. Furthermore, we noticed an improvement of all Key Performance Indicators, among them:

- RTCH assignment failure: (depends mainly on the TCH signal quality): 0.38 % down to 0.32%, meaning 16,5% improvement

- Call drop rate (depends mainly on the TCH signal quality): 0.61% down to 0.51 %, meaning 17% improvement

- Quality handover rate (depends mainly on the TCH signal quality). There has been a spectacular improvement (from 45 % to 30%: 33% improvement) that is reported in the chart below:

These results prove that the new frequency plan leads to a reduced interference level. It results in a significant improvement of the quality of the network. Discrete Frequency Hopping could be applied as well to preserve the quality while performing capacity extension through new transceivers or while shrinking the allocated spectrum.

Number of TCH TRXs

Number of hopping frequencies

1 42 43 44 55 56 6



5. CONCLUSION Discrete Frequency Hopping is a field-proven method to optimise an operator’s spectrum.

It makes it possible to allocate the optimal number of hopping frequencies and to apply the optimal frequency allocation, leading then to good network KPIs even with high RF loads. RMS provides field measurements collected by the Base Stations and the Mobiles in the

field. Those measurements are used to perform an automated and optimised Frequency Planning. This one can be based on Base Band Hopping, Synthesized Frequency Hopping or Discrete Frequency Hopping. Introducing RMS and/or DFH frequency planning is done by software only and is a fast

and cost-efficient means of dramatically improving network KPIs even in highly loaded networks. Discrete Frequency Hopping and/or RMS may be applied to improve the network quality while keeping the same load and the same spectrum or to preserve the quality while extending the network by adding more TRXs in each cell or reducing the spectrum (e.g. in case of GSM and UMTS sharing the same spectrum). Related Documents: Design Paper – Densification of GSM Networks Design Paper – Spectrum Planning in GSM/GPRS/EDGE FUNCTIONAL FEATURE DESCRIPTION - Radio Measurement Statistics (RMS) - MAFA in Release B7

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