Faculty of Engineering and Information Technologies

Laboratory 2: Analysis of Measurement Data
Aims:
This laboratory is for the students to gain skills
to analyse raw measurement data
that have been recorded from a live LTE network. St
udents will represent raw data in
well-presented graphical formats and analyse the me
asurement results using Excel and/or
MATLAB.
Outline:
Section 1 – Introduction to Laboratory and Paramet
er Definitions
Section 2 – Laboratory Exercises
Appendix A – MATLAB Codes
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Section 1: Introduction to Laboratory and Parameter
Definitions
The measurement was conducted using a “NEMO Handy”
in the same network as
Laboratory 1. The attached file (Lab2_Data.xls) con
tains a measurements of a LTE
handset downloading a file. The handset was moving
at a pedestrian speed from an area
with a good signal quality to the cell boundary whe
re there is no adjacent cell to hand-
over to (death-spot). The LTE network used is Tel
stra LTE with a bandwidth of 10 MHz
which is equivalent to 50 PRBs as per Laboratory 1.
Parameter Definitions:
RSRP (Reference Signal Received Power)
The RSRP measurement provides a cell-specific signa
l strength metric. This
measurement is used mainly to rank different LTE ca
ndidate cells according to their
signal strength and is used as an input for handove
r and cell reselection decisions. RSRP
is defined for a specific cell as the linear averag
e over the power contributions (in Watts)
of the Resource Elements (REs) which carry cell-spe
cific RS within the considered
measurement frequency bandwidth. Normally the RS tr
ansmitted on the first antenna port
are used for RSRP determination, but the RS on the
second antenna port can also be used
if the UE can determine that they are being transmi
tted. If receive diversity is in use by
the UE, the reported value is the linear average of
the power values of all diversity
branches.
Refer also 3GPP TS 36.214 subclause 5.1.1.
Range: -140 – 0
Unit: dBm
RSRQ (Reference Signal Received Quality)
This measurement is intended to provide a cell-spec
ific signal quality metric. Similarly to
RSRP, this metric is used mainly to rank different
LTE candidate cells according to their
signal quality. This measurement is used as an inpu
t for handover and cell reselection
decisions, for example in scenarios for which RSRP
measurements do not provide
sufficient information to perform reliable mobility
decisions. The RSRQ is defined as the
ratio:
RSRQ = N · RSRP/(LTE carrier RSSI),
where N is the number of Resource Blocks (RBs) of t
he LTE carrier RSSI measurement
bandwidth. The measurements in the numerator and de
nominator are made over the same
set of resource blocks. While RSRP is an indicator
of the wanted signal strength, RSRQ
additionally takes the interference level into acco
unt due to the inclusion of RSSI. RSRQ
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therefore enables the combined effect of signal str
ength and interference to be reported in
an efficient way.
The measurements in the numerator and denominator a
re made over the same set of
resource blocks. Refer also 3GPP TS 36.214 subclaus
e 5.1.3.
Range: -30 – 0
Unit: dB
RSSI (Carrier Received Signal Strength Indicator)
Carrier RSSI (frequency scanning mode)
The LTE carrier RSSI is defined as the total receiv
ed wideband power observed by the
UE from all sources, including co-channel serving a
nd nonserving cells, adjacent channel
interference and thermal noise within the measureme
nt bandwidth . LTE carrier RSSI is
not reported as a measurement in its own right, but
is used as an input to the LTE RSRQ
measurement described below.
Range: -140 – -10
Unit: dBm
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Section 2: Laboratory Exercises
As part of the lab submission, the students should
submit a report containing graphs, and
answers of the following questions.
1. Plot the following graphs (for antenna port 1 an
d port 2 where applicable):
– RS SNR vs measurement slots
– RSRP vs measurement slots
– RSRQ vs measurement slots
– RSSI vs measurement slots
1.a Compare RSRP and SNR graphs. Express the differ
ence and similarity of the trends
of these graphs. [20]
Hint: Plot a graph showing the relationship betwee
n RSRP and SNR (RSRP minus
SNR in dB) which can provide an approximation of th
e interface level. You may use
either MS Excel or MATLAB to create the graphs. Sel
ect the corresponding columns
in the Excel data. In MATLAB, use the codes below:
Figure(11)
SNR=[x1];
% Replace x1 by data in Column H in the Lab2_Data (
SNR)
plot(SNR)
title(
‘SNR vs Measurement Slots’
)
xlabel(
‘Measurement Slots’
)
ylabel(
‘SNR in dB’
)
Adjust the codes accordingly for other parameters.
1.b Compare the trends of RSRP, RSRQ and RSSI and p
rovide explanation. [15]
2. Plot the following graphs:
– Throughput vs measurement slots
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– The relationship between SNR (x-axis) and through
put (y-axis).
Hint: Plot graph in logarithm scale (x-axis in dB a
nd semilog in y-axis using semilogy in
MATLAB). Use the following codes:
Figure(20)
semilogy(SNR,throughput)
% SNR in the data in Columm H and
throughput is in Column K
title(
‘SNR vs Throughput’
)
xlabel(
‘SNR in dB’
)
ylabel(
‘Throughput in bps’
)
Make sure the SNR used is a larger value between SN
R values on Antenna port 1 and
port 2 in each measurement slot
2.a Find the maximum and minimum throughput (consid
er the measurement slots [20:180])
[10]
Hint: Use following MATLAB commands
– max(x) and find(x==max(x))
– min(x([20:180])) and find(x==min(x[20:180]))
Make sure you find the maximum (and minimum) throug
hput and its
corresponding measurement slot(s)
2.b Find the value of SNR at which the throughput s
tarts to degrade (i.e. when the
throughput is lower than 10 Mbps for more than 10 m
easurement slots). Explain how
the result relates to RSRP level. [15]
2.c Consider the measurement slots that the lowest
throughout occurs (t
min
) and when the
peak throughput occurs (t
max
). Plot the following graphs for each t
min
and t
max
:
– PRB percentage.
– Modulation percentage
Compare and analyse the results. [20]
Hint: Use similar data to the following. The measur
ement slots should be as obtained
from Question 2.a.
% Example Data from Measurement Slot 78
% modmax=[2 2 2 2 6 6 6 6 2 2 2
2 2 4 4 4
4 4 4 6 6 6 6 6 6 6 6];
% pmodmax=[54.7 2.4 4 0.2 0.3 0.2 0.2 0.2 1.1 0.3
0.3 0.3 0.3 0.3 0.2
0.6 1.8 2.3 5.2 9.9 3.7 5.5 1.8 1 0.3 1.3 1 0.6
];
% nrb=[0 3 6 9 12 15 27 29 30 33 36
38 39 41 42 44
45 47 48 50];
% prb=[54.7 6.8 0.2 0.2 0.5 0.2 0.2 0.6 0.2 0.2 0.2
0.2 3.6 0.3 1.3 0.3
0.2 3.4 1.3 25.7];