-Medical surveillance is based on continuous monitoring of the patients vital parameters. The control of vital signs is essential in different cases. Actually, in the case of criticals healths issues (road or traffic accident; Pregnancy and pregnancy-related complication like blood pressure, foetal heart rate, etc...) vitals parameters need to be continually measured. Imagine the case where the patient is living in a rural area or remote area with poor health infrastructure. That kind of situation needs the involvement of news technologies (telemedicine, IoT), technics to help to overcome the medical service delivery issues. Base on this background and due to the technologies issues and limitations in some area or region the authors had proposed a new technology to support the medical service delivery at a remote area. The proposed technology consisted of Narrowband Internet of Things (NB-IoT). Its a new technology which provides longrange communications, low data rate for sensors with reduced device processing complexity and long battery lifetime.This paper aims to investigate the realistic performance of NBIoT in terms of effective throughput and patient served per cell in the healthcare monitoring system in a rural area with in-band and stand-alone deployment. Index Terms-Narrowband Internet of Things (NB-IoT); Healthcare monitoring; throughput; latency; device capacity; system-level analysis.
The last quarter century has been a period of huge change
and progress in developing countries. Never the less this
impressive progress, health access remains limited for many
people especially, in rural area and slums in the large city.
In fact, in Low and Middle-Income Countries (LMIC), the
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health sector is facing some challenges ( lack of skills, but
also a shortage of health personnel and even worse, a lack of
health centres). These issues are more several in the rural area.
This compromises the provision, continuity and availability of
care and services for the habitats of these areas. As a result,
the populations in the areas face inadequate health care due to
shortage or poor distribution of financial and human resources
and a shortage of specialized services. Specialists often do not
have enough ”critical mass” of patients to be economically
profitable to serve a region that is both sparsely populated
and far away. The situation can be particularly difficult for
patients with certain diseases, or for the elderly. Information
and communication technology solutions, such as e-health,
telemedicine, etc ... can be seen as ways to bridge the digital
divide between rural and urban health centers and address
deficiencies health sector in rural areas[
Design a tractable wireless sensor network (NB-IOT) system to coordinate patient follow-up in a rural area of Benin;
To suport the Internet of Things, a narrowband system
based on Long Term Evolution (LTE) is introduced in 3rd
Generation Partnership Project (3GPP) [
Narrowband reference signal (NRS); Narrowband primary and secondary synchronization signals (NPSS and NSSS); Narrowband physical downlink control channel (NPDCCH); Narrowband physical downlink shared channel (NPDSCH).
In the uplink, NB-IoT support both single-and multi-tone transmissions. Furthermore, in NB-IoT uplink, a new resource mapping unit is defined as a resource unit (RU). RU is a combination of a number of subcarrier (frequency domain) and a number of slots (time domain). For the uplink, NB-IoT has one physical signal and two physical channels which are as follows:
Demodulation reference signal (DMRS); Narrowband physical random access channel (NPRACH); Narrowband Uplink Shared Channel (NPUSCH).
NB-IoT has been developed by 3GPP to enable a wide range
of cellular devices and services [
III. APPLICATION USE-CASE: HEALTH CARE
MONITORING SYSTEM
In hospitals, the temperature of a patients body, for instance, need to be monitored constantly, which is generally made by the staff members of the hospital. They notice the temperature of the patients body constantly and keeps a record of it. Health monitoring means monitoring a person to identify any changes in his or her health status because of exposure to certain health hazards arising from the conduct of the business or undertaking (GRWM Regulations). Health monitoring is a way to check if the health of workers is being harmed from exposure to hazards while carrying out work, and aims to detect early signs of ill-health or disease. Health monitoring can show if control measures are working effectively. Monitoring does not replace the need for control measures to minimise or prevent exposure. Nowadays, health care sensors are playing an essential role in hospitals. The patient monitoring system is one of the major developments because of its innovative technology. An automatic wireless health monitoring system is used to measure the patients body temperature and heartbeat by using embedded technology.
The use of NB-IoT allows the use of an already deployed
cellular base station and covers all facilities in
underdeveloped countries, eg rural hospitals. NB-IoT offers end-user
terminals (eg sensor nodes) a long service life. However, each
application is characterized by different coverage requirements
and performance requirements in terms of tattoo demand or
latency. For example, health usually requires monitoring of
perspiration, respiratory rate, body temperature, pulse and
blood pressure, etc. Data rates of up to 2 Kbps per sensor may
be required. In our design model of the health care monitoring
system, we consider the single-sensor nodes. In this design,
each sensor node, such as a temperature sensor, a respiratory
rate sensor, etc., is considered an individual node and each
node has its own transmission module. Therefore, each node
transmits data to the central processing unit through the eNB
with latency and data rate requirements [
IV. METHODOLOGY, DATA AND SYSTEM MODEL
To conduct the performance analysis, we have considered both in-band and standalone deployments of NB-IoT with a bandwidth of 180 kHz in a typical LTE. The scenario is a regular grid of tri-sector sites with inter-site distance of 1732m. In-band mode, for instances where cellular services are present and NB-IoT is positioned in the LTE carrier sharing LTE resources; this mode of operation is perhaps the more costeffective and seamless for mobile operators since it does not require any hardware changes of the radio access network, and efficiently uses spectrum resources for LTE or NB-IoT services based on demand from mobile users or devices. In Standalone mode, for instances where cellular services are not present or are decommissioned to make narrowband spectrum available, which is the case of cellular GSM; by reframing one or more GSM carriers to carry NB-IoT traffic, operators can ensure a smooth transition to LTE for massive machine type communication. The Fig 2 illustrate the deployment of in-band and Stand Alone.
The other simulation assumptions that closely follows are
presented in Table1. The full 180 kHz bandwidth, i.e. 12
subcarriers at 15 kHz subcarrier spacing in both downlink and
uplink, is used for the analysis. For uplink, this is known to
perform worse than single tone e.g. 3.75 kHz or 15 kHz, so
the achieved performance in this study yields lower bounds as
compared to what can be achieved with single tone NB-IoT
systems and it is more realistic assumption to investigate
NB-IoT uplink performance[
SIN Ri;n =
Pnhi;n
Ii;n + N0
(2)
where Pn is the transmit power and hi;n is the channel
gain between node i and the base station on the nth PRB.
Ii;n is the interference experienced by node i and is assumed
to be negligible in our analysis. N0 is the noise power
spectral density. Based on the SINR, the corresponding MCL
is computed. The relationship between SINR and MCL is
given as [
T argetSIN R = Txpower + 174 N oisef igure (3) 10log10(B)
M CL
P athLoss = I + 37:6log10(R) (4) R in Kilometers with I=120.9 for the 900 Mhz
The inter-arrival time is distributed over three categories
of periodic transmissions with constant inter-arrival times of
1 day, 2 hours, 1 hour and 30 minutes. Based on [
In this section, we evaluate the performance of the NB-IoT system-level system using Monte Carlo simulations in terms of actual throughput and the number of devices supported. With the parameters shown in Table 1, the simulation is run for band and standalone deployments for more than 750 random samples. Figure 3 illustrates the cumulative distribution function (CDF) of the average effective flow in different strip and stand-alone deployments. The actual rate is defined as the number of bits of information transmitted per second with all the control information headers. The tape deployment performance in terms of battery life is significantly degraded due to the presence of LTE control information and the
TABLE I
SIMULATION ASSUMPTION assumptions different interferences due to the two coexisting systems. Figure 4 shows the average number of patients that can be treated in different deployment scenarios. The result is that autonomous deployment is an important way to dramatically improve the flow and number of patients in care.
In this article, we presented a detailed performance analysis specific to a NB-IoT application for a rural health care surveillance system. The analysis carried out shows that with the autonomous deployment, one observes a significant gain in flow and a large number of patients per cell compared to the deployment in band. From these results, we can conclude that the NB-IoT technology is better suited for monitoring patients in rural areas, due to precarious conditions such as lack of electricity and medical infrastructure. Based on the results of this work, we can in terms of perspectives, work to precisely determine the geolocation of patients and evaluate different resource management strategies in NB-IoT rural systems.