LTE Network Coverage Prediction for Multi-traffic Users in an Urban Area

LTE Network Coverage Prediction for Multi-traffic Users in an Urban Area

Md. Maruf Ahamed1, Zahirul Islam2, Sehtab Hossain3and Saleh Faruque, PhD4

Department of Electrical Engineering The University of North Dakota

Grand Forks, ND 58203 E-mail: [email protected], [email protected],[email protected],

[email protected]

Abstract— Due to the advancement of telecommunication platform, users are now demanding new applications such as Online Gaming, mobile TV, Web 2.0, and to meet this requirement operators needed to design more flexible network. For the deployment of this network, 3rd Generation Partnership Project (3GPP) works on the Long Term Evolution (LTE) and propose a system which has larger bandwidths (up to 20 MHz), low latency and packet optimized radio access technology having peak data rates of 100 Mbps in downlink and 50 Mbps in the uplink [3,4]. Radio access technology for LTE is OFDM (Orthogonal frequency division multiplexing) which provides higher spectral efficiency and more robustness against multipath fading, as compared to CDMA (Code division multiple access). Offering a greater coverage by providing higher data rates over wider areas and flexibility of use at existing and new frequency bands plan is a major challenge. In this paper, we are analyzing practical coverage scenario in an urban area (i.e. Kolkata) in terms of received signal levels, total noise, interference, throughput, and quality factor for downlink signal level.

Index Terms- LTE, Throughput, Coverage, Downlink signal level.

I. INTRODUCTION System specific parameters like, transmit power of the

antennas, their gains, estimate of system losses, type of antenna system used etc, must be known prior to the start of wireless cellular network dimensioning. Each wireless network has its own set of parameters.

Traffic analysis gives an estimate of the traffic to be carried by the system. Different types of traffic that will be carried by the network are modeled. Traffic types may include voice calls, VOIP, PS or CS traffic. Overheads carried by each type of traffic are calculated and included in the model. Time and amount of traffic is also forecasted to evaluate the performance of the network and to determine whether the network can fulfill the requirements

set forth. Coverage estimation is used to determine the coverage area of each base station.

Coverage estimation calculates the area where base station can be heard by the users (receivers). It gives the maximum area that can be covered by a base station. But it is not necessary that an acceptable connection (e.g. a voice call) between the base station and receiver can be established in coverage area. However, base station can be detected by the receiver in coverage area.

Coverage planning includes Radio Link Budget (RLB) and Coverage analysis. For the planning of any Radio Access Networks begins with a RLB. RLB comprises the accounting of all gains and losses from the transmitter end (Base Station Site), through the medium (i.e. free space, cable, waveguide, fiber, etc.) to the receiver end (Mobile Station) in a Telecommunication System. The maximum allowed receive signal level at the mobile station to the base station is estimated which allows to calculate the maximum path loss allows to get maximum cell range that leads to estimate a suitable Propagation Model. According to the cell range, it allows to estimate the total number of base station sites required to cover a required geographical area.

Fig.1. General radio link budget of radio network

II. COVERAGE ANALYSIS Coverage analysis gives the estimation of the resources

needed to provide service in the deployment area with specific system requirements. In this section, the cell radius

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of a particular LTE sector is calculated based on the propagation environment.

Fig.2. Receive Signal Level at a distance d from base station

The received signal level is defined as the signal strength

received at a distance d (Km) and is given by the link budget equation in a the wireless channel as follows:

PRX = PTX + GTX + GRX – LTX – LRX + PM - LP (1) Where, the PRX is the received power (dBm). PTX is

the transmitted output power (dBm). GTX and GRX is transmitter and receiver antenna gain (dBi), respectively. LTX and LRX are the cable and other losses on the transmitter and receiver side (dB) respectively. PM is the planning margin and LP is the path loss between transmitter and receiver end.

The path loss criteria are solely depends on the propagation environment. According to Okumura-Hata Propagation model there are four different types of propagation environment and considering each propagation environment there is a propagation model.

1. Dense Urban Model 2. Urban 3. Sub-Urban 4. Rural The path loss formula is given by [16]. Lp(dB)=C0+C1+C2 log(FMHZ)-13.82 log(Hb)-a(Hm) +[44.9-6.55 log(Hb)] log(dKm) (2) Where C0, C1 and C2 are constants and are given:

C0 = 0 for Urban = 3 dB for Dense Urban C1 = 69.55 for 150 MHz to 1000 MHZ = 46.30 for 1500 MHz to 2000 MHz C2 = 26.16 for 160 MHz to 1000 MHZ = 33.90 for 1600 MHz to 2000 MHz

F = Frequency in MHz d = Distance (cell radius) in Km Hb = Base station antenna height in meters Hm = Mobile Antenna height in meters For Urban, a(Hm) ={1.1 log (FMHz) - 0.7}Hm – {1.56 log (FMHz) – 0.8} (3) For Dense Urban, a(Hm) = 3.2[log{11.75 Hm }]2 – 4.97 (4)

From equation (2) we can find the cell radius: dKm= anti log [{Lp(dB)-C0-C1-C2 log(FMHZ)+13.82 log(Hb)+ a(Hm)}/ {44.9-6.55 log(Hb)}] (5) So the coverage area of one sector in LTE can be calculated

as: Coverage Area = (π d2)/number of sectors (6)

III. REQUIRED SINR The basic performance indicator of LTE radio network is

‘Required SINR’. Maximum allowed path loss is calculated according to the condition [15]:

SINR ≥ Required SINR (7) SINR = (AveRxPower)/(Interference+RxNoise) (8) Where, SINR is Signal to Interference and Noise Ratio.

AveRxPower is Average Received Power (W). Interference is Interference Power (W) which comprises Own Channel Interference (i.e., Power due to own cell interference) and Other Cell Interference (i.e., Power received for neighboring cells). RxNoise is receiver noise power which includes Thermal noise and Receiver Noise figure.

IV. AVERAGE CELL THROUGHPUT CALCULATIONS To maximize the capacity of any coverage area we need

to have cell throughput under certain constraints which depends upon the SINR occurrence probability. The average cell throughput is derived as follows [15]:

Cell Throughput = ∑all SINR values (SINR Occurrence Probability * Average Throughput SINR) (9)

Where, SINR Occurrence Probability is the Probability of occurrence of a specific SINR value at cell edge obtained using simulation. Average Throughput SINR is Average throughput corresponding to SINR value.

V. SIGNAL QUALITY MEASURES Coverage is defined as the possibility to get a service

with a defined network requirement in terms of signal quality. This section is described three major signal quality that is available, RSRP (Reference Symbol Received

Power), RSRQ (Reference Symbol Received Quality) and CQI (Channel Quality Indicator) [15].

A. RSRP (Reference Symbol Received Power) RSRP is a signal strength measurement and

it is used for Handover and cell reselection purposes but also for signal attenuation measurements for UL (Uplink) power control and random access. The signal attenuation can be calculated as follows:

Lsa = PRS,RE – RSRP (10) Where, Lsa is the signal attenuation between the TX

(Transmitter) reference point and the UE (User Equipment) [dB]. PRS,RE is the power per resource element of the reference signal [dBm] at the TX reference point.

PRS,RE is depends on the available power and the bandwidth:

PRS,RE = Pnom,ref – 10 log(ηRB) – 10 log (12) (11) Where, Pnom,ref is the total power in the TX reference

point. For instance, if we have two Radio Units of 20W each then Pnom,ref is equal to 40W minus any feeder loss. And, ηRB is the number of resource blocks in the system bandwidth.

For the simulation we have used 20 MHz bandwidth, 40 W (46dBm) of available power and 3dB feeder loss, so PRS,RE is:

PRS,RE = 46 – 3 – 10*log(100) - 10*log(12) = 12.208dBm

The following Table 1 shows Rough Classification of

RSRP for transmitter power of 13 dBm.

Table 1 Rough Classification of RSRP

Classification RSRP Lsa Good Above -95dBm Below 108 dB Medium -95 to -108 dBm 108 to 121 dB Poor Below -108 dBm Above 121 dB

B. RSRQ (Reference Symbol Received Quality)

RSRQ is calculated as: RSRQ = RSRP + 10 log(ηRB) – RSSI (12) Where, Received Signal Strength Indicator (RSSI) is the

wide band interference measured over all resource blocks. RSRQ is dependent on the load in the own cell as well as the interference from other cells.

The following equation describes the relation for a MIMO (Multiple Input Multiple Output) configuration:

RSRQ = γmean – 10 log[12+(4+8QDL)10γmean/10] (13) where, γmean is the average signal-to-interference-ratio

over the symbol when transmission occurs. QDL is the downlink load level in the own cell at the symbols where RSRQ is evaluated. When no user traffic is present then

QDL=0 and when all resource blocks are used with user traffic then QDL=1.

The following table shows the classification of RSRQ when the load is zero.

Table 2

Rough Classification of RSRQ Assuming No Load in Cell Classification RSRQ Good Above -7dB Medium -7 to -10 dB Poor Below -10 dB

C. CQI (Channel Quality Indicator)

Due to the strong load dependence, it can be difficult to use RSRQ to classify the radio environment. An alternative is to use CQI measurements. CQI measurements are mandatory measurements of the channel quality and can be used to estimate the expected downlink rates. However, CQI measurements are UE dependent.

VI. ANALYSIS OF LTE COVERAGE FOR KOLKATA CITY Digital Map of Kolkata city including height, clutter and

vector map are shown in the following figure:

Fig.3. Digital map of Kolkata city

The following coverage predictions are based on the

received downlink reference signal levels: • Coverage by Transmitter • Coverage by Signal Level • Overlapping Zones These coverage predictions do not depend on the traffic

input. Therefore, these calculations are of special interest before and during the deployment stage of the network to study the coverage footprint of the system. The resolution of

the coverage prediction does not depend on the resolutions of the path loss matrices or the geographic data and can be defined separately for each coverage prediction. Coverage predictions are generated using a bilinear interpolation method from multi-resolution path loss matrices (similar to the one used to calculate site altitudes).

Coverage predictions have been performed by: Best receive signal level, downlink throughput and Channel to Interference plus Noise Ratio (CINR) and in terms of quality indicator. Coverage prediction properties: (a) channel throughput (DL), (b) Downlink C/(I+N), (c) Coverage by Quality Indicator (DL), (d) by best signal level have been shown in Fig. 4 to Fig.11.

Fig.4. Effective coverage area by (UL+DL) signal level

For the simplicity of analyze we are choosing particular

area of KOLKATA city that covers by Cell Site namely Site8, Site12, Site13, Site 14, Site15, and Site16. The following figure depicts the effective service area by uplink and downlink signal level strength.

Fig.5. Coverage prediction by throughput (DL signal level)

Quality-related inputs include average cell throughput

and blocking probability. These parameters are the customer requirements to provide a certain level of service to its users. The channel efficiency concept refers to gain as

higher throughput as possible utilizing an available channel bandwidth.

Fig.6. Coverage prediction by throughput properties

Fig.7. Coverage prediction C/(I+N) Level (DL)

Coverage prediction is greatly affected by the received

signal levels, total noise integrated to this signal and different type of interferences like inter channel and co-channel interference.

Fig.8. Coverage prediction by Coverage by C/

Fig,9. Coverage prediction by Quality Ind

/(I+N) properties

dicator (DL)

Fig.10. Coverage pre

Fig.11. Overlapping

VII. SIMULATION PAR

Here we have shown the sconsidered for the coverage pr

T

Simulati

IX. CONCLUSION A Purpose of Dimensioning determining the areas that needof number of sites required t

ediction by best signal level

g zone by best signal level

RAMETER CONSIDERATION simulation parameter which we rediction:

able 3 ion Parameter

AND FUTURE WORK or Radio network planning is

d to be covered and computation to serve the target areas while

fulfilling the coverage and capacity requirements. AS it in above the maximum coverage is obtained when there is minimum path loss or less signal attenuation. But in case of urban area the signal is attenuated rapidly as distance from base station to mobile station rises. Optimization such as tilting and antenna redirections can improve the coverage and capacity significantly. Another way to maximize coverage area is to increase the power of Radio Base Station. The ultimate objective of our research to analyze the major factors that affect coverage prediction considering a real field scenario and it will assist the estimation of core network planning and back haul requirement. Decision is made about few parameters in dimensioning phase. For example, target MCS, BLER, BS configuration, e.g. 3-sector/omni, antenna types, MIMO type etc.

REFERENCES

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