What is HSN and MAIO in GSM?

Today let's understand what are the parameters MAIO and HSN in a GSM network.

The terms MAIO and HSN are also often used, but many people are confused about it's planning. That's right, HSN and MAIO are used in frequency planning of a GSM network, and know them well naturally will lead us to better results.

Quickly: The HSN is used to define the hopping sequence from one frequency list, and MAIO is used to set the initial frequency on this list.

It did not help? So come on and try to understand better ...

Note: The goal here is not to teach HSN and MAIO planning, since this task involves many possible configurations and scenarios, which would escape the scope of our tutorial. The main goal today is to understand, in a planning already deployed, what they mean values MAY HSN and assigns.

Frequency Hopping e MA List

To understand how HSN and MAIO are used in planning, we first need to know some brief concepts.

• Frequency Hopping – or FH: one of the great advantages of the GSM system, in the constant search to reduce interference. More on the FH due to a new tutorial.

• MA List: set of frequencies (channels) assigned to a particular sector, ie are those channels that can be used to attend calls from users.

To illustrate, let's consider a sector with 4 TRX, where the first TRX is used for BCCH and the others are TCH TRX.

The MA List with the channels of traffic then would be:

HSN e MAIO

Sure, with the example in mind, let us return to our parameters.

First, the definition of HSN: Hopping Sequence Number. It is a number that defines the frequency hopping algorithm, and can vary from 0 to 63, ie there are 64 hopping algorithms to be used in GSM.

If HSN is zero, the frequency hopping sequence is cyclic, ie without changes.

If HSN is greater than zero, then frequencies vary pseudo-randomly.

When we enabled the Hopping - our case - all TRX in the SAME SECTOR has the SAME HSN. And if the we have 1x1 SFH it is recommended to have the SAME HSN for ALL SECTORS of the BTS.

In our example, the MA List is small - just three frequencies. The size of the MA List should be taken into account in the planning of HSN: HSN should be the designated so as to minimize the average probability of collision, according to the designated MAIOs.

And how MAIO's are designed?

Well, first defining MAIO: Mobile Allocation Index Offset. It's MAIO that designate the initial position of frequency - among the frequencies available in MA List, that list with the frequency hopping. It is the frequency that TRX uses so get hopping.

MAIO planning is straightforward if the number of TRX is small compared to the length of the sequence of hopping.

For example, MAY 0 means that the TRX should use the first frequency, or f1.

GSM Automatic Frequency Planning Tools

The concept of HSN and MAIO is important, and when the number of TRX and frequencies is small, we can even do planning 'byt hand'.

However, the best way - and always recommended - is to use network planning tools suitable for this purpose, as the AFP, from Optimi, or Ultima Forte, from Scheme.

These tools can be configured with measurements collected from the network (via BSS and / or Drive Test ), and with predictions (calculations) built in that allow the creation of a Interference Matrix. Based on this matrix, along with other algorithms, it allow a better design of parameters based on such critical conditions in traffic load and access. According to characteristics of each sector, they then provide the final planning, including the possibility of simulations.

Conclusion

Knowing the concept of HSN and MAIO we can use them correctly in our plans, and/or do audits of our existing networks. For example, in two hopping sequences, if we have the same HSN and different MAIO, we guarantee that they never overlap, or in other words, are orthogonal.

Another conclusion is that two channels with different HSN, but with the same MA List and at the same time slot, will interfere with 1 / n of bursts, where n equals the number of different frequencies in the hopping sequence. This conclusion is somewhat more complex to see, and is due to feature pseudo randomly from HSN. So if you have interest, deepen their studies of MAY and HSN. Otherwise, just understand that it is why we say that the Frequency Hopping somehow averages the interference across the network.

Creating and Editing Drive Test Routes in Google Earth

Definition of Quality Routes

Quality routes are pre-defined pathways, and that must be performed periodically, usually 2 to 2 months.

These routes should cover the relevant areas of the network, such as large customers and companies, bridges and major Avenues, etc.

Long ago, these routes were marked in printed maps, and delivered to the staff responsible for perform the Drive Test.

Currently it is more common the creation and use of these routes in vector files, lines drawn on GIS programs such as Mapinfo and Google Earth.

As an example, via Google Earth, we can use the 'Add Path' button, and build our path, the path we want for the quality route. (To simplify our example, our route here will be pretty simple).

We navigate until our region of interest, and after doing some edits, our route is ready to be sent to the test drive execution team.

However, even on that route so simple, we can make some comments, or improvements.

First, we must remember that the routes will be travelled by people, who do not always know the region with details. This includes knowing the direction, points of departure and arrival, etc.

In addition, routes can be travelled by different people, from time to time.

Another important point: perhaps the desired route, exactly the way it was designed, may not be possible to be travelled.

The ideal is to have these routes perfectly defined, taking into account the criteria mentioned above. So you do not need to repeat the recommendations for each new performer.

And how to do this?

The best way to define Drive Test routes is drawing the same observing all existing conditions. In other words, plot the routes so that is really what we'll find in the road.

The route that we use as example allows us to see clearly what this means.

In 'red' we have the 'original' route, which was designed according to our needs. And in 'blue', the 'possible' route, driving by allowed roads. This is a route 'validated' by Google Maps routes.

But how to draw this type of route with accuracy?

Although Google Earth does not allow editing routes, we can do this using Google Maps!

Once set (and adjusted) the route on Google Maps, we can save it as a 'kml' file, and use it later in our work in Google Earth.

Creating a route in Google Maps

Next, we'll demonstrate how the route above was created in Google Maps, and also how this final adjusted route was saved as a 'kml' file to be used in Google Earth.

The key information here is that Google Maps allows dynamic adjustment of drawn routes, making automatic correction of directions to the new 'allowed' points.

To do so, simply move the mouse over any point on the route, and so appear a small circle, move it to the new desired intermediate point.

But let's go, and see how we made this route.

First, visit Google Maps.

Continuing, we typed an address from our route, for example where we want to start - 'A' point. Then we typed the same address as a point 'B', and finally click on the 'Get Directions' button.

We have then a first 'route', from point 'A' to point 'B' – which for the moment is the same point.

Note: Yes, you can type the same address, as we'll change the end point 'B'.

Then, continuing we click in point 'B', and we drag it in the direction of our desired route.

As you move the point, an 'X' (1) shows where it can be released, that is, where will the temporary endpoint be. We also have dynamic information with information of it (2).

Depending on your route, you can go by dragging the point to a location farther at route, and Google Maps will automatically be recalculating it, also indicating on the map.

But if you drag too far, the route will be 'recalculated' for the best possible route – the best route to drive from one point to another. However, this may not be our goal, because we want the route passing through places that we chose.

For example, if you drag the point too far, the route may differ too much from the objective.

The solution?

To solve this problem, and be able to set the route for specific points, we drag the end point 'B' to a point where the route still follow what we want.

Temporarily dropping point 'B', we pass the mouse over the route (at a point near it). At this time, there is a small white circle (1), indicating that we can 'Drag' the route to modify it (edit).

In our case, we are don't want to edit the route, but we can use this gimmick to 'force' the Google Maps to include this point on our route. In order to not change the route, click and drag this point to another point – on the same route, and very close to where you moved your mouse and saw the circle.

Note that at this time, this crossing point is indicated also on the left side of the map (just like the small white circle on the map).

Note: when you insert a new crossing point, you have the option to undo. To do this, just click on 'Undo' at the top right of the map. If you don't do so, you will no longer be able to remove it in edit mode (you can only remove it all). But don't worry, an exit if you want to remove a point is drag it to a point that already exists.

Ok, now we drag point 'B' to a point near the starting point 'A', and our route is created.

Using the tips above, you can now create any customized route, adding how many intermediate points are necessary.

Once you have created a route, click on the 'Link' button (1), copy the URL (2) to the Clipboard and save to a text file.

Note: you can also edit the routes adding new destinations (point 'c', point 'd', etc.). If you want to use in this way, use the sidebar, which allows changing the order of items via 'drag & drop'.

If you would like more information, watch the video:

http://www.youtube.com/watch?v=KPOOWvP_dd8&feature=player_embedded#!

Editing a route in Google Maps

To edit a route, the steps are the same as shown above: simply create and drag the new crossing points, from the desired points.

Again, note that the route is always automatically calculated, observing all existing variables like traffic. If you want to change, just as we saw above, inserting new crossing points.

Using the (saved) route in Google Earth

Fine, we already have our saved route in Google Maps (just paste the URL you copied in any browser). But to use our route in Google Earth, we need to save it as a 'kml' file.

To do this, the procedure is also simple: add text ‘&output=kml’ at the end of the URL.

Paste this URL into a browser, press 'Enter', and the output is in the Google Earth format (kml).

Save this route (kml file) in an appropriate location, and use according to your needs in Google Earth. Note: always keep the URL's of their routes in text files, so when you need to change it just paste in Google Maps and go back to edit.

By right-clicking on the route, you still have the option to edit it, for example, change the color and opacity.

Done: your route is ready to be used!

Conclusion

This was a brief overview of how to create and edit routes on Google Maps and Google Earth.

We learn how simple is to create routes like professionals. Adding intermediate points, we have total control of the final form of our route.

In addition, the route generated (calculated) by Google Maps already takes into account local conditions such as traffic.

If you liked this tip, encourages us to continue bringing always the best content for enhance your work: share telecomHall with your friends!

And if possible, leave your comment, just below. Until our next meeting!

Convert Drive Test Log to Google Earth Thematic Map

Hi readers, I would like to share another case of converting drive test (DT) logfiles to be viewed in Google Earth, but this time with thematic color. Some of you guys should know how to create thematic map using Mapinfo or DT post processing tools such as Actix or Nemo Analyzer. Using this kind of thematic maps showing the distribution of signal strength or quality is a common way to understand the network behavior and their problem. It is going to be more exciting to combine thematic maps overlayed in Google Earth.

In this article, I am going to show you how to export logfile data from TEMS Investigation to thematic KML.

1. Export Logfiles to TXT

First, we need to export collected logfiles into .txt file. Choose Text file in the Format dropdown, then on the Setup->Export to Text File window select the Information Elements that you need. Longitude and Latitude is mandatory. In the example, we choose RxLevSubdBm and RxQual. After that simply choose the desired logfiles and let TEMS do the rest.

2. Using MS Access

After the export process finished, we will find the exported TXT file on the targeted directory. We can use Excel to open it. But if the file size is large, then Access is the right option. Let’s open the exported TXT using Access. First, you need to create blank database by clicking on File->New…->Blank Database. The database has been created, now we need to import the exported TXT file into the database. Right click on the Table then choose Import. For Access 2007 users use External Data then choose Text File.

Locate the exported TXT then the Import Text Wizard will appear. ChooseDelimited then click Next. On the Choose the delimiter that separates your fields: choose Tab. Put a check on First Row Contains Field Names and choose Text Qualifier as {None}. Click Next.

On the next window just choose In a New Table. Click Next.

Click Next again. On the next window choose No primary key. Click Next.

Put a name in the Import to Table: field then Finish. Access will import it to a new table.

Now, we need to do simple query. Choose Create query in Design View or click the Design toolbar. Put the table into the query and put the MS, Longitude, Latitude, and RxLev Sub dBm to the fields. On the Criteria fillMS1 or desired MS for choosing the MS/UE we desire. Put also Is not null on the All RxLev Sub dBm’s criteria to select non blank data.

Press CTRL + S to save the query and give a unique name such as RxLev. Run the query and you should see something like this:

Now right click on the query, RxLev in this example and choose Export… Give a name and choose Text File in the Save as Type. Click Export.
Choose Delimited. Next.
Choose Comma  as the delimiter, put a check in the Include Field Names on First Row, and Text Qualifier=None.
In the Export to File rename the .txt extension into .csvFinish.

Exporting CSV into Thematic KML

We need csv2kml, a fantastic tools created by CoverageTools. You can download it for free in their site or click here.

After installing this software just run it and choose File->Open CSV to locate our CSV file.

On the Source Data choose the IE, for example All-RxLev Sub (dBm).
On the Latitude select Latitude.
On the Longitude select Longitude.

We can set our standard Range Values. For example:

Just put out-of-range fields with value such as -999. What about the color? The easiest way to set the color is click on Save Values after you set the range. Then, simply go to C:\Program Files\coveragetools\csv2kml and open the saved .VAL using Notepad. It is going to be like this:

RSSI [dBm]
 6 
-68,0,347235
-72,-68,00FF00
-76,-72,D0F52F
-80,-76,F5000A
-89,-80,1F8FE
-105,-89,100FE
-999,-105,FFFFFF
-999,-999,FFFFFF
-999,-999,FFFFFF
-999,-999,FFFFFF
Basestation
 10 
 0 ,7B1284
 1 ,6FB490
 2 ,66F799
 3 ,25EADA
 4 ,ADEA52
 5 ,F1700E
 6 ,B10B4E
 7 ,61069E
 8 ,1C81E3
 9 ,5EDFA

Simply change the hexadecimal value according to the desired color. You can refer to this for color hexadecimal value.

Ready for the result? Just click Export button, KML file will be saved in the same directory of the CSV file. Give it a double click and you can see it on Google Earth!

Quick Recap of MIMO in LTE and LTE-Advanced

The following is from NTT Docomo Technical journal (with my edits):

MIMO: A signal transmission technology that uses multiple antennas at both the transmitter and receiver to perform spatial multiplexing and improve communication quality and spectral efficiency.

Spectral efficiency: The number of data bits that can be transmitted per unit time and unit frequency band.

In this blog we will first look at MIMO in LTE (Release 8/9) and then in LTE-Advanced (Release-10)

MIMO IN LTE

Downlink MIMO Technology

Single-User MIMO (SU-MIMO) was used for the downlink for LTE Rel. 8 to increase the peak data rate. The target data rates of over 100 Mbit/s were achieved by using a 20 MHz transmission bandwidth, 2 × 2 MIMO, and 64 Quadrature Amplitude Modulation (64QAM), and peak data rates of over 300 Mbit/s can be achieved using 4×4 SU-MIMO. The multi-antenna technology used for the downlink in LTE Rel. 8 is classified into the following three types.

1) Closed-loop SU-MIMO and Transmit Diversity: For closed-loop SU-MIMO transmission on the downlink, precoding is applied to the data carried on the Physical Downlink Shared Channel (PDSCH) in order to increase the received Signal to Interference plus Noise power Ratio (SINR). This is done by setting different transmit antenna weights for each transmission layer (stream) using channel information fed back from the UE. The ideal transmit antenna weights for precoding are generated from eigenvector(s) of the covariance matrix of the channel matrix, H, given by HHH, where H denotes the Hermitian transpose.

However, methods which directly feed back estimated channel state information or precoding weights without quantization are not practical in terms of the required control signaling overhead. Thus, LTE Rel. 8 uses codebook-based precoding, in which the best precoding weights among a set of predetermined precoding matrix candidates (a codebook) is selected to maximize the total throughput on all layers after precoding, and the index of this matrix (the Precoding Matrix Indicator (PMI)) is fed back to the base station (eNode B) (Figure 1).

LTE Rel. 8 adopts frequency-selective precoding, in which precoding weights are selected independently for each sub-band of bandwidth from 360 kHz to 1.44 MHz, as well as wideband precoding, with single precoding weights that are applied to the whole transmission band. The channel estimation used for demodulation and selection of the precoding weight matrix on the UE is done using a cell specific Reference Signal (RS) transmitted from each antenna. Accordingly, the specifications require the eNode B to notify the UE of the precoding weight information used for PDSCH transmission through the Physical Downlink Control Channel (PDCCH), and the UE to use this information for demodulation.

LTE Rel. 8 also adopts rank adaptation, which adaptively controls the number of transmission layers (the rank) according to channel conditions, such as the received SINR and fading correlation between antennas (Figure 2). Each UE feeds back a Channel Quality Indicator (CQI), a Rank Indicator (RI) specifying the optimal rank, and the PMI described earlier, and the eNode B adaptively controls the number of layers transmitted to each UE based on this information.

2) Open-loop SU-MIMO and Transmit Diversity: Precoding with closed-loop control is effective in low mobility environments, but control delay results in less accurate channel tracking ability in high mobility environments. The use of open-loop MIMO transmission for the PDSCH, without requiring feedback of channel information, is effective in such cases. Rank adaptation is used, as in the case of closed-loop MIMO, but rank-one transmission corresponds to open-loop transmit diversity. Specifically, Space-Frequency Block Code (SFBC) is used with two transmit antennas, and a combination of SFBC and Frequency Switched Transmit Diversity (FSTD) (hereinafter referred to as “SFBC+FSTD”) is used with four transmit antennas. This is because, compared to other transmit diversity schemes such as Cyclic Delay Diversity (CDD), SFBC and SFBC+FSTD achieve higher diversity gain, irrespective of fading correlation between antennas, and achieve the lowest required received SINR. On the other hand, for PDSCH transmission with rank of two or higher, fixed precoding is used regardless of channel variations. In this case, cyclic shift is performed before applying the precoding weights, which effectively switches precoding weights in the frequency domain, thereby averaging the received SINR is over layers.

3) Adaptive Beamforming: Adaptive beamforming uses antenna elements with a narrow antenna spacing of about half the carrier wavelength and it has been studied for use with base stations with the antennas mounted in a high location. In this case beamforming is performed by exploiting the UE Direction of Arrival (DoA) or the channel covariance matrix estimated from the uplink, and the resulting transmit weights are not selected from a codebook. In LTE Rel. 8, a UE-specific RS is defined for channel estimation in order to support adaptive beamforming. Unlike the cell-specific RS, the UE specific RS is weighted with the same weights as the data signals sent to each UE, and hence there is no need to notify the UE of the precoding weights applied at the eNode B for demodulation at the UE. However, its effectiveness is limited in LTE Rel. 8 because only one layer per cell is supported, and it is an optional UE feature for Frequency Division Duplex (FDD).

Uplink MIMO Technology

On the uplink in LTE Rel. 8, only one-layer transmission was adopted in order to simplify the transmitter circuit configuration and reduce power consumption on the UE. This was done because the LTE Rel. 8 target peak data rate of 50 Mbit/s or more could be achieved by using a 20 MHz transmission bandwidth and 64QAM and without using SU-MIMO. However, Multi-User MIMO (MU-MIMO) can be used to increase system capacity on the LTE Rel. 8 uplink, using multiple receiver antennas on the eNode B. Specifically, the specification requires orthogonalization of the demodulation RSs from multiple UEs by assigning different cyclic shifts of a Constant Amplitude Zero Auto-Correlation (CAZAC) sequence to the demodulation RSs, so that user signals can be reliably separated at the eNode B. Demodulation RSs are used for channel estimation for the user-signal separation process.

MIMO TECHNOLOGY IN LTE-ADVANCED

Downlink 8-Layer SU-MIMO Technology

The target peak spectral efficiency in LTE-Advanced is 30 bit/s/Hz. To achieve this, high-order SU-MIMO with more antennas is necessary. Accordingly, it was agreed to extend the number of layers of SU-MIMO transmission in the LTE-Advanced downlink to a maximum of 8 layers. The number of transmission layers is selected by rank adaptation. The most significant issue with the radio interface in supporting up to 8 layers is the RS structure used for CQI measurements and PDSCH demodulation.

1) Channel State Information (CSI)-RS: For CQI measurements with up-to-8 antennas, new CSI-RSs are specified in addition to cell-specific RS defined in LTE Rel. 8 for up-to-four antennas. However, in order to maintain backward compatibility with LTE Rel. 8 in LTE-Advanced, LTE Rel. 8 UE must be supported in the same band as in that for LTE-Advanced. Therefore, in LTE Advanced, interference to the PDSCH of LTE Rel. 8 UE caused by supporting CSI-RS must be minimized. To achieve this, the CSI-RS are multiplexed over a longer period compared to the cell-specific RS, once every several subframes (Figure 3). This is because the channel estimation accuracy for CQI measurement is low compared to that for demodulation, and the required accuracy can be obtained as long as the CSIRS is sent about once per feedback cycle. A further reason for this is that LTE-Advanced, which offers higher data-rate services, will be developed to complement LTE Rel. 8, and is expected to be adopted mainly in low-mobility environments.

2) UE-specific RS: To allow demodulation of eight-layer SU-MIMO, the UE-specific RS were extended for SU-MIMO transmission, using a hybrid of Code Division Multiplexing (CDM) and Frequency Division Multiplexing (FDM) (Figure 4). The UE-specific RS pattern for each rank (number of layers) is shown in Figure 5. The configuration of the UE-specific RS in LTE-Advanced has also been optimized differently from those of LTE Rel.8, extending it for SU-MIMO as well as adaptive beamforming, such as by applying twodimensional time-frequency orthogonal CDM to the multiplexing between transmission layers.

Downlink MU-MIMO Technology

In addition to the peak data rate, the system capacity and cell-edge user throughput must also be increased in LTE-Advanced compared to LTE Rel. 8. MU-MIMO is an important technology for satisfying these requirements. With MU-MIMO and CoMP transmission (described earlier), various sophisticated signal processing techniques are applied at the eNode B to reduce the interference between transmission layers, including adaptive beam transmission (zero-forcing, block diagonalization, etc.), adaptive transmission power control and simultaneous multi-cell transmission. When these sophisticated transmission techniques are applied, the eNode B multiplexes the UE-specific RS described above with the PDSCH, allowing the UE to demodulate the PDSCH without using information about transmission technology applied by the eNode B. This increases flexibility in applying sophisticated transmission techniques on the downlink. On the other hand, PMI/CQI/RI feedback extensions are needed to apply these sophisticated transmission techniques, and this is currently being discussed actively at the 3GPP.

Uplink SU-MIMO Technology

To reduce the difference in peak data rates achievable on the uplink and downlink for LTE Rel. 8, a high target peak spectral efficiency of 15 bit/s/Hz was specified for the LTE-Advanced uplink. To achieve this, support for SU-MIMO with up to four transmission antennas was agreed upon. In particular, the two-transmission-antenna SU-MIMO function is required to satisfy the peak spectral efficiency requirements of IMT-Advanced.

For the Physical Uplink Shared Channel (PUSCH), it was agreed to apply SU-MIMO with closed-loop control using multiple antennas on the UE, as well as codebook-based precoding and rank adaptation, as used on the downlink. The eNode B selects the precoding weight from a codebook to maximize achievable performance (e.g., received SINR or user throughput after precoding) based on the sounding RS, which is used for measuring the quality of the channel transmitted by the UE. The eNode B notifies the UE of the selected precoding weight together with the resource allocation information used by the PDCCH. The precoding for rank one contributes to antenna gain, which is effective in increasing cell edge user throughput. However, considering control-information overhead and increases in Peak-to-Average Power Ratio (PAPR), frequency-selective precoding is not very effective in increasing system throughput, so only wideband precoding has been adopted.

Also, for rank two or higher, when four transmission antennas are used, the codebook has been designed not to increase the PAPR. The demodulation RS, which is used for channel estimation, is weighted with the same precoding weight as is used for the user data signal transmission. Basically, orthogonalization is achieved by applying a different cyclic shift to each layer, but orthogonalizing the code region using block spread together with this method is adopted.

Uplink Transmit Diversity Technology

Closed-loop transmit diversity is applied to PUSCH as described above for SU-MIMO. Application of transmit diversity to the Physical Uplink Control Channel (PUCCH) is also being studied. For sending retransmission request Acknowledgment (ACK) and Negative ACK (NAK) signals as well as scheduling request signals, application of Spatial Orthogonal-Resource Transmit Diversity (SORTD) using differing resource blocks per antenna or an orthogonalizing code sequence (cyclic shift, block spread sequence) has been agreed upon (Figure 6). However, with LTE-Advanced, the cell design must be done so that LTE Rel. 8 UE get the required quality at cell-edges, so applying transmit diversity to the control channels cannot contribute to increasing the coverage area, but only to reducing the transmission power required.