<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">CN</journal-id><journal-title-group><journal-title>Communications and Network</journal-title></journal-title-group><issn pub-type="epub">1949-2421</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/cn.2021.133008</article-id><article-id pub-id-type="publisher-id">CN-111505</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Computer Science&amp;Communications</subject></subj-group></article-categories><title-group><article-title>
 
 
  Scenario Based Transmission Power Control (TPC) Analysis over Wireless Body Area Network (WBAN)
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Taslim</surname><given-names>Arefin</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Mohammad</surname><given-names>Hanif Ali</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>A.</surname><given-names>K. M. Fazlul Haque</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib></contrib-group><aff id="aff2"><addr-line>Department of ETE, Daffodil International University, Dhaka, Bangladesh</addr-line></aff><aff id="aff1"><addr-line>Department of CSE, Jahangirnagar University, Dhaka, Bangladesh</addr-line></aff><pub-date pub-type="epub"><day>04</day><month>08</month><year>2021</year></pub-date><volume>13</volume><issue>03</issue><fpage>93</fpage><lpage>110</lpage><history><date date-type="received"><day>20,</day>	<month>March</month>	<year>2021</year></date><date date-type="rev-recd"><day>23,</day>	<month>August</month>	<year>2021</year>	</date><date date-type="accepted"><day>26,</day>	<month>August</month>	<year>2021</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  In the modern age, Wireless Body Area Network (WBAN) becomes very popular everywhere for monitoring healthcare services remotely. However, the WBAN system has lagged in efficient power consumption till now. As WBAN is formed with several portable devices, low power consumption will ensure battery lifetime. In this paper, an analysis of Transmission Power Control (TPC) over WBAN has been conducted. A ZigBee based WBAN model with different network topologies and data rates has been proposed in the experiment. WBAN data-management technique has been proposed due to reducing more data transmission. Less data transmission reduces overall power consumption. The whole work has been done using OPNET and OMNET++ network simulators. Six sensor nodes have been used with a ZigBee coordinator in the simulation scenario where throughput, load, delay, data traffic, amount of power consumption, packet delivery ratio, etc. have been used as simulation parameters. TPC analysis indicates the power consumptions in different topologies, with different data rates. Several simulation scenarios were run and the results were analyzed in this paper.
 
</p></abstract><kwd-group><kwd>WBAN</kwd><kwd> ZigBee</kwd><kwd> TPC</kwd><kwd> Power Control</kwd><kwd> Transmission Power</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Through modern-day technology, services and applications, it has become easy to save human lives via providing far better monitoring for health care services. Thus, electronic health care was created to serve such a purpose, the system has several health care applications and it’s referred to as the e-health system [<xref ref-type="bibr" rid="scirp.111505-ref1">1</xref>]. Furthermore, this technology can provide a better health care service for the patient’s everyday status, by creating associate increased manner of observation and taking care of patients in their natural setting at their homes or anyplace else in each day’s life. Also, the exploitation the wireless technology can give associate improved period observation within the future [<xref ref-type="bibr" rid="scirp.111505-ref2">2</xref>]. Being aforementioned that, wireless body area network (WBAN) consists of a variety of sensors that area unit either ingrained within the patient’s body or wearable convenience as an example a monitor watch, to live that person’s health stats. Additionally, it’s vital to say here that sensors should be made by considering the subsequent features: lightweight Wight, small size, optimum power consumption, and low value [<xref ref-type="bibr" rid="scirp.111505-ref3">3</xref>]. <xref ref-type="fig" rid="fig1">Figure 1</xref> shows a wireless body area network. Moreover, the sensors area unit referred to as nodes within the system and the area unit connected to a getaway, the entranceway is accountable being an instrumentality to the network, helping to transfer information to the medical server and store it within the patient’s file [<xref ref-type="bibr" rid="scirp.111505-ref4">4</xref>]. It’s vital to say that, WBAN is taken into account one of the still rising technologies beneath its progress phases associated it’s beneath an early stage of development, and it is expected to be at some point a stable system utilized in the health care applications.</p><p>WBAN has recently received a lot of attention for its application to the assisted remote patient observance and living. WBAN contains wireless devices that are secured to the soma to observe a large variety of physical quantities. The character of those wireless sensors permits nice ﬂexibility in their movement. New sector square measure gap for these technologies in medical and health observance service, e.g. period mensuration of pulse, body temperature, and pressure level, etc. Analysis of life signals in patients with chronic conditions [<xref ref-type="bibr" rid="scirp.111505-ref5">5</xref>].</p><p>Like Wireless Sensor Networks (WSNs) applications, the power consumption of WBAN nodes is so essential. In health observance, all sensor nodes should operate for a long period of time as a result of charging isn’t potential and also the choice of optimum transmission power becomes vital. Several WBAN applications</p><p>send frames comparatively more frequently that sometimes resulting in exaggerated channel estimation error. The IEEE 802.15.6 unit has the difficult readying problems with WBANs and has developed a new customary for targeting wireless communications in and around the soma space. It deﬁnes because the physical and link layers for WBANs, however, don’t specify a TPC rule for WBANs [<xref ref-type="bibr" rid="scirp.111505-ref5">5</xref>].</p><p>The device nodes in the WBAN unit are powered by energy-restricted batteries, so reducing energy consumption becomes a necessary issue to be addressed. Although power consumption decreases with the event of low-power physical science technology, the energy efficiency drawback can’t be ignored for WBAN with the most transmission distance of 3 m or 5 m inside the past few years, a variety of energy-saving ways in which and measures square measure planned and studied. The proposed model associated with energy efficiency rule is expected to minimize the transmission energy of communication systems well as increase the transmission length time [<xref ref-type="bibr" rid="scirp.111505-ref6">6</xref>].</p></sec><sec id="s2"><title>2. Methodology</title><p>WBAN will works in two ways in the initial stage.</p><p>a) Sensor Node;</p><p>b) Gateway Node.</p><p>1) Sensor Nodes</p><p>Sensor nodes are implanted on the human body. They are placed on the surface or inside the body and gather information from the human body and pass it through gateway nodes. <xref ref-type="fig" rid="fig2">Figure 2</xref> shows a dummy illustration of sensor nodes implanted on the surface of the human body.</p><p>2) Gateways Node</p><p>The gateway node shown in <xref ref-type="fig" rid="fig3">Figure 3</xref> is responsible for conveyance device info to medical servers or doctors. Failure of the entry node suggests that failure of the WBAN system of a patient. Thus, extending the lifetime of the gateway node may be a fascinating objective in coming up with WBAN systems [<xref ref-type="bibr" rid="scirp.111505-ref7">7</xref>].</p><p>WBAN is designed specifically for medical systems and for emergency things. In such things, the little detector nodes within the network collect very important data using a sensor from the body and upload it to the medical server within the hospital. <xref ref-type="fig" rid="fig4">Figure 4</xref> shows a typical WBAN architecture. This data is then examined by a doctor or a medico within the hospital for identification. The communication within the WBAN is secured as a result of this network uses physiological values (PVs) that are personal human information. This may alter higher attention facilities. Lack of security measures can result in incorrect detection that is risky for human life.</p><p>WBAN uses cryptographical keys to secure communication. Bluetooth key distribution theme is employed that is of various sorts.</p><p>The main difference between WBAN and WSN has a power and memory management system. The security protocol also is different among them. Security issues also major in WBAN due to monitoring accurately. The most drawback with this security theme is that the risk (of data of knowledge) leak as throughout key agreement this theme exchange quite needed information.</p><p>For example, the whole feature sets square measure changed between human action sensors mistreatment this theme. If the sender and also the receiver have</p><p>the feature sets the same, then they’ll use a standard key. This key may be simply generated by AN outsider World Health Organization acquires of these feature sets [<xref ref-type="bibr" rid="scirp.111505-ref8">8</xref>].</p></sec><sec id="s3"><title>3. Transmission Power Control</title><p>The TPC section in WBAN is a major part of a model due to the power consumption issue. To design WBAN model power efficiency is given the most priority. For that reason, TPC management needed to improve. It can be done by three steps [<xref ref-type="bibr" rid="scirp.111505-ref9">9</xref>]:</p><p>&#183; At first, we need to improve the constancy of a link. A constant link increases transmission power.</p><p>&#183; Secondly, the nodes that are connected in a constant area need to minimize collision among the interconnected nodes. More collisions reduce transmission power.</p><p>&#183; Finally, proposed transmission power is given to the model for better performance of the channel. Here a good modulation technique works best for energy saving. Controlled transmission power is preferable here.</p><p>1) The ZigBee Stack:</p><p>A simple view of ZigBee showed in <xref ref-type="fig" rid="fig5">Figure 5</xref>. This system will be worked out in our simulation.</p><p>&#183; Physical Layer (PHY);</p><p>&#183; Madia Access Control (MAC);</p><p>&#183; Network (NWK);</p><p>&#183; Application Support (APS);</p><p>&#183; Security Service Provider (SSP);</p><p>&#183; ZigBee Device Object (ZDO);</p><p>&#183; Application Framework (APF).</p><p>2) Bio Signal Packet Transmission:</p><p>A bio-signal is collected from the human body using a sensor node. Medical adjusted with a specific area in the human body. According to the condition of</p><p>the patient these signals are divided into three categories [<xref ref-type="bibr" rid="scirp.111505-ref10">10</xref>].</p><p>a) Urgent: Data collected from the critical condition of a patient is called urgent data. For example, a patient’s blood pressure is 160 mmHg or getter, this data from the blood pressure sensor is called urgent data. It is given the most priority because this condition is more sensitive. For this reason, this condition sensor node collects data continuously.</p><p>b) Semi-urgent: This type of bio-signal some less important than an urgent data signal. For example, ECG gives the result of heartbeats near 60 bpm. It is not normal but more important the normal. At any time have a chance to go a patient critical condition. This condition is given medium priority.</p><p>c) Non-urgent: This type of bio-signal is considered less important. When a patient is in a normal condition or a completely healthy man, it is not important to measure his blood pressure continuously. The sensor node can be given a time interval to reduce power consumption.</p></sec><sec id="s4"><title>4. Implementation and Results</title><p>Simulations and results demonstrate the performance of star, mesh, cluster-tree topologies in different performance parameters and those are throughput, delay, load, data traffic sent, data traffic received, packet dropped so that simulation and result part is an important approach to evaluating the work. To develop a real-time scenario of a project work instead of simulation model work it must be requiring more time, financial cost, and effort through a simulation model that doesn’t need to present necessarily appropriate. But the main object of any simulation model is to properly portend the behavior of real scenarios [<xref ref-type="bibr" rid="scirp.111505-ref11">11</xref>].</p><p>For design ZigBee model many simulators can be proposed but, in this research, used OPNET simulator and OMNET++ for analysis power control. OPNET has an academic version known as Riverbed and OMNET++ is an open-source network simulator that represents graphically interface.</p><p>In this paper, the OPNET is used to design mesh, star, and cluster topologies with 250kbps and 1024 kbps data rate. In this project work was designed with ZigBee sensor nodes.</p><p>1) Scenario: Simulation of different topologies at 250 kbps data rate in the noiseless area</p><p>Firstly, here is discussed with 6 sensor nodes and 250 Kbps data rates for mesh topology. Here is considered a hospital environment like ICU. Here noise is too low and it fixed around 40 kbps per sensor. For 6 sensors need around 250 kbps calculated. Finally, the amount of data transmitted will be 2025 kbps per node.</p><p><xref ref-type="fig" rid="fig6">Figure 6</xref> contains star topology with 6 sensor nodes, router, ZigBee coordinator, and user applications. Star topology applied with a 250 kbps data rate.</p><p><xref ref-type="fig" rid="fig7">Figure 7</xref> contains 6 sensor node, router, ZigBee coordinator. Cluster topology is applied here with a 250-kbps data rate.</p><p>a) Throughput</p><p>Throughput describes how fast the total number of data successfully sends</p><p>and received a physical layer from MAC. Throughput also is the actual measurement of data send using communication channels [<xref ref-type="bibr" rid="scirp.111505-ref12">12</xref>].</p><p><xref ref-type="fig" rid="fig8">Figure 8</xref> represents that which topology gives better performance. In 1224 seconds, the maximum throughput values have been obtained 59.22 kbps, 94.16 kbps in 1764 second, and 63.49 kbps in 918 seconds for the cluster, mesh and star topologies respectively.</p><p>b) Delay</p><p>The delay means the amount of extra time compares with actual processing time on the communication channel. It reduces channel accuracy or efficiency. A small amount of delay prefers for better performance [<xref ref-type="bibr" rid="scirp.111505-ref13">13</xref>].</p><p>In above <xref ref-type="fig" rid="fig9">Figure 9</xref>, the minimum delay has been recorded in the cluster, mesh, and star topologies are 0.0128 sec, 0.0127 sec, and 0.0143 sec respectively. The minimum delay of these topologies gives the best result.</p><p>c) Load</p><p>Load refers to the amount of total data traffic being carried among the</p><p>communication channel in data communication. The performance of a communication channel will be better at a low load.</p><p>In <xref ref-type="fig" rid="fig1">Figure 1</xref>0, it has been shown the amount of load with 250 kbps data rate in the cluster, mesh, and star topologies. The maximum load is shown in mesh topology 29.175 kbps and cluster, star topology respectively 22.925, 22.865 kbps.</p><p>d) Data Dropped for Different Data Rate</p><p>The amount of data that cannot be transmitted through a channel called data dropped. It was held due to failure ACK of the MAC protocol for retransmit data. A large number of data dropped to reduce the performance of a channel.</p><p>In <xref ref-type="fig" rid="fig1">Figure 1</xref>1 when time starts 0-sec data dropped was Zero and at 1782 sec data dropped was 1.519 kbps for the cluster, 3.544 kbps for mesh, 4.923 kbps for the star.</p><p>e) Data Traffic Sent</p><p>Data traffic is that the quantity information of knowledge of information moving across a network channel. The amount of data traffic sent measured the performance of a channel. As much as the high amount of data traffic sent this</p><p>result will be best.</p><p>For 250 kbps data rate the <xref ref-type="fig" rid="fig1">Figure 1</xref>2 is has been shown that cluster-tree gets 23.32 kbps, 29.320 kbps for mesh and star gets 18.51 kbps data traffic received by MAC from the physical layer.</p><p>2) Scenario 2: Simulation of different topology at 1024 kbps/1Mbps data rate</p><p><xref ref-type="fig" rid="fig1">Figure 1</xref>3 contains 6 sensor node, ZigBee coordinator, user applications, etc. Here used a 1024 kbps data rate with a mesh topology.</p><p><xref ref-type="fig" rid="fig1">Figure 1</xref>4 contains 6 sensor nodes, ZigBee coordinator, user applications, etc. Here used a 1024 kbps data rate with star topology.</p><p><xref ref-type="fig" rid="fig1">Figure 1</xref>5 contains 6 sensor node, ZigBee coordinator and user applications, etc. Here used a 1024 kbps data rate with cluster topology.</p><p>a) Throughput</p><p>In <xref ref-type="fig" rid="fig1">Figure 1</xref>6, the maximum throughput values have been obtained in 64.088 kbps in 90 seconds for the cluster, 55.372 kbps in 36 seconds for mesh, and 50.17 kbps in 72 seconds for star topologies.</p><p>b) Delay</p><p>In <xref ref-type="fig" rid="fig1">Figure 1</xref>7, the minimum delay has been recorded in the cluster, mesh, and star topologies are 0.012111 sec, 0.009399 sec, and 0.01360035 sec in 18, 18, and 36 sec respectively.</p><p>c) Load</p><p>In <xref ref-type="fig" rid="fig1">Figure 1</xref>8, the maximum load has been recorded in the cluster, mesh, and star topologies are 29.200 kbits/sec, 23.555 kbits/sec, and 12.672 kbits/sec</p><p>in 108, 72 and 126 sec respectively.</p><p>d) Packet drop Dropped</p><p>In this <xref ref-type="fig" rid="fig1">Figure 1</xref>9, the value of packet drop has been gained in the cluster, mesh, and star topologies are 513.87 bits/sec, 956.4444 bits/sec, and 4274.2222 bits/sec in 18 sec respectively.</p><p>e) The Packet Sent</p><p>In above <xref ref-type="fig" rid="fig2">Figure 2</xref>0, packet sent for cluster-tree 26.40 kbps, mesh 25.95 kbps and star 14.3 kbps at 379 sec, 1171 sec, and 1170 sec respectively.</p><p>f) Packet Received</p><p>In above <xref ref-type="fig" rid="fig2">Figure 2</xref>1, cluster-tree 197.359 kbps, mesh 204.17 kbps and star</p><p>118.11 kbps received data at 144 sec, 1171 sec, and 666 secs respectively.</p><p>3) Scenario 3: Simulation with data segmentation techniques</p><p>There are several techniques used in WBAN technology. Data segmentation is one of them. In this technique data, it is classified into three categories according to the importance of data types. This scenario compared the data segmentation technique compared with other two existing techniques [<xref ref-type="bibr" rid="scirp.111505-ref3">3</xref>] [<xref ref-type="bibr" rid="scirp.111505-ref6">6</xref>]. <xref ref-type="table" rid="table1">Table 1</xref> gives the different parameters and values to configure all parameters.</p><p>PACKET DELIVERY RATIO</p><p>The packet delivery ratio means the number of packets is different from the transmitter and receiver. It ensures channel quality.</p><p><xref ref-type="fig" rid="fig2">Figure 2</xref>2 shows that packet transmission in simulation time 1000 s, the 2000 s, and 3000 s. The power consumption rate increasing is with simulation time rapidly. The data classification method is better than the existing QoS-aware and Anomaly detection method.</p><p><xref ref-type="fig" rid="fig2">Figure 2</xref>3 shows that power consumption of oxygen sensor increasing according to simulation time. Data segmentation techniques reduce more data transmission increasing simulation time as like sleeping method.</p><p>In <xref ref-type="fig" rid="fig2">Figure 2</xref>4, the power consumption of the blood pressure sensor has been shown. Here the power consumption has a significant reduction in the proposed system comparing two reference models. Performance Analysis is the method of learning or evaluating the performance of a selected situation as compared</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> The configuration of parameters</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Parameter</th><th align="center" valign="middle" >Value</th></tr></thead><tr><td align="center" valign="middle" >Arrangement type</td><td align="center" valign="middle" >Static (transmission. continuously)</td></tr><tr><td align="center" valign="middle" >Sensor loads</td><td align="center" valign="middle" >loads 1.0 p/s,.2 p/s, and 10 p/s</td></tr><tr><td align="center" valign="middle" >No. of sensor</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle" >Sensor Energy</td><td align="center" valign="middle" >100 mW</td></tr><tr><td align="center" valign="middle" >Gateway Energy</td><td align="center" valign="middle" >100 mW</td></tr><tr><td align="center" valign="middle" >Buffer packet size</td><td align="center" valign="middle" >One packet</td></tr><tr><td align="center" valign="middle" >Simulation time</td><td align="center" valign="middle" >1000 s, 2000 s, 3000 s</td></tr><tr><td align="center" valign="middle" >Sensor Type</td><td align="center" valign="middle" >ECG, SpO2 and Blood pressure</td></tr></tbody></table></table-wrap><p>to the target that was to be achieved. Performance analysis is often neutralizing finance on the premise of ROI, profits, etc. Here performance will be analyzed for differences in real-time scenarios. In the first scenario mesh, star, and cluster topologies are simulated in the 250 kbps data rate.</p><p><xref ref-type="fig" rid="fig2">Figure 2</xref>5 shows that, the performance of mesh topology is best for data transmission. The efficiency of a channel reduces transmission power consumption. So, mesh topology is the best to consider TPC analysis.</p><p>In data of <xref ref-type="fig" rid="fig2">Figure 2</xref>6, the rate was the same (1 mbps) for cluster-tree, mesh, and star topology but data transmission rate better in Mesh.</p></sec><sec id="s5"><title>5. Conclusion</title><p>A new simulation methodology of WBANs transmission power control analysis has been presented in the paper. In the first scenario mesh, star, and cluster topologies are simulated in 250 kbps data rate using ZigBee at different topologies. Only three topologies are used here because the IEEE802.15.4 standard (ZigBee) only supports the cluster, mesh, star topologies. Here focused on the power control analysis of ZigBee sensor nodes using OPNET and OMNET++ simulators in this paper. To test the performance of the topologies, this paper simulated or analyzed them for different types of scenarios. Here analysis with different data rates for creating a different environmental situation and find low power consuming topology. Mesh topology is best to consider TPC analysis for throughput, data traffic sent and received. Also, for 1024 kbps data rate mesh was better for the delay and data traffic received. So it can be said that mesh topology is the best. The data segregation technique is also more effective for reducing power consumption. The results outperform the best model to reduce power consumption that extends battery life. In wireless technology another major subject is security. Violate attacks may be a dangerous issue for WBAN medical services or others. The amount of power consumed can be increased due to gateway failure. By implementation of a collision reduce the technique between the warning and welcome back packets of the gateway to improving the packet delivery ratio of the introduced gateway failure algorithm. Also, develop a Security protocol is a challenge for WBAN.</p></sec><sec id="s6"><title>Conflicts of Interest</title><p>The authors declare no conflicts of interest regarding the publication of this paper.</p></sec><sec id="s7"><title>Cite this paper</title><p>Arefin, T., Ali, M.H. and Haque A.K.M.F. (2021) Scenario Based Transmission Power Control (TPC) Analysis over Wireless Body Area Network (WBAN). Communications and Network, 13, 93-110. https://doi.org/10.4236/cn.2021.133008</p></sec><sec id="s8"><title>NOTES</title></sec></body><back><ref-list><title>References</title><ref id="scirp.111505-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Zhang, H. and Safaei, F. (2018) Channel Autocorrelation-Based Dynamic Slot Scheduling for Body Area Networks. EURASIP Journal on Wireless Communications and Networking, 2018, Article No. 246. https://doi.org/10.1186/s13638-018-1261-8</mixed-citation></ref><ref id="scirp.111505-ref2"><label>2</label><mixed-citation publication-type="other" xlink:type="simple">Archasantisuk, S., Aoyagi, T., Kim, M. and Takada, J.I. (2016, September) Transmission Power Control in WBAN Using the Context-Specific Temporal Correlation Model. 2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Valencia, Spain, 4-8 September 2016, 1-6.</mixed-citation></ref><ref id="scirp.111505-ref3"><label>3</label><mixed-citation publication-type="other" xlink:type="simple">Archasantisuk, S., Aoyagi, T., Kim, M. and Takada, J.I. (2018) Temporal Correlation Model-Based Transmission Power Control in a Wireless Body Area Network. IET Wireless Sensor Systems, 8, 191-199. https://doi.org/10.1049/iet-wss.2016.0109</mixed-citation></ref><ref id="scirp.111505-ref4"><label>4</label><mixed-citation publication-type="other" xlink:type="simple">Fernandes, D., Ferreira, A.G., Abrishambaf, R., Mendes, J. and Cabral, J. (2017) Survey and Taxonomy of Transmissions Power Control Mechanisms for Wireless Body Area Networks. IEEE Communications Surveys &amp; Tutorials, 20, 1292-1328. https://doi.org/10.1109/COMST.2017.2782666</mixed-citation></ref><ref id="scirp.111505-ref5"><label>5</label><mixed-citation publication-type="other" xlink:type="simple">Di Franco, F., Tachtatzis, C., Atkinson, R.C., Tinnirello, I. and Glover, I.A. (2014) Channel Estimation and Transmit Power Control in Wireless Body Area Networks. IET Wireless Sensor Systems, 5, 11-19. https://doi.org/10.1049/iet-wss.2013.0070</mixed-citation></ref><ref id="scirp.111505-ref6"><label>6</label><mixed-citation publication-type="other" xlink:type="simple">Zhengl, Z., Zheng, X., Tian, J. and Shu, M. (2018, May) A Transmission Power Control Algorithm for Wireless Body Area Networks. 2018 IEEE 22nd International Conference on Computer Supported Cooperative Work in Design (CSCWD), Nanjing, China, 9-11 May 2018, 854-858.</mixed-citation></ref><ref id="scirp.111505-ref7"><label>7</label><mixed-citation publication-type="other" xlink:type="simple">Rahman, A. and Khan, N. (2016, August) Optimum Placement of Gateway Node on the Human Body for Real-Time Healthcare Monitoring Using WBAN. 2016 Sixth International Conference on Innovative Computing Technology (INTECH), Dublin, Ireland, 24-26 August 2016, 408-412.</mixed-citation></ref><ref id="scirp.111505-ref8"><label>8</label><mixed-citation publication-type="other" xlink:type="simple">Barakah, D. M. and Ammad-uddin, M. (2012, February) A Survey of Challenges and applications of Wireless Body Area Network (WBAN) and Role of a Virtual Doctor Server in Existing Architecture. 2012 Third International Conference on Intelligent Systems Modelling and Simulation, Kota Kinabalu, Malaysia, 8-10 February 2012, 214-219.</mixed-citation></ref><ref id="scirp.111505-ref9"><label>9</label><mixed-citation publication-type="other" xlink:type="simple">Jafari, R. and Effatparvar, M. (2017) An Overview on the Transmission Power Control. The International Journal of Computer and Information Technologies (IJOCIT), 5, 43-51.</mixed-citation></ref><ref id="scirp.111505-ref10"><label>10</label><mixed-citation publication-type="other" xlink:type="simple">Abiodun, A. S., Anisi, M.H., Ali, I., Akhunzada, A. and Khan, M.K. (2017) Reducing Power Consumption in Wireless Body Area Networks: A Novel Data Segregation and Classification Technique. IEEE Consumer Electronics Magazine, 6, 38-47. https://doi.org/10.1109/MCE.2017.2715518</mixed-citation></ref><ref id="scirp.111505-ref11"><label>11</label><mixed-citation publication-type="other" xlink:type="simple">Denis, B., Amiot, N., Uguen, B., Guizar, A., Goursaud, C., Ouni, A. and Chaudet, C. (2014, December) Qualitative Analysis of RSSI Behavior in Cooperative Wireless Body Area Networks for Mobility Detection and Navigation Applications. 2014 21st IEEE International Conference on Electronics, Circuits and Systems (ICECS), Marseille, France, 7-10 December 2014, 834-837.</mixed-citation></ref><ref id="scirp.111505-ref12"><label>12</label><mixed-citation publication-type="other" xlink:type="simple">Benolirao, J.A., de Joya, A.J., Lim, I., Osayta, L.K. and Cordel, M. (2016, May) Quantifying the Throughput and Latency Contribution in Secured IEEE 802.15. 6 WBAN Simulated Transmission. 2016 IEEE Region 10 Symposium (TENSYMP), Bali, Indonesia, 9-11 May 2016, 305-310.</mixed-citation></ref><ref id="scirp.111505-ref13"><label>13</label><mixed-citation publication-type="other" xlink:type="simple">Roblin, C. (2011, September) Analysis of the Channel Power Delay Profile of WBAN Scenarios in Various Indoor Environments. 2011 IEEE International Conference on Ultra-Wideband (ICUWB). Bologna, Italy, 14-16 September 2011, 545-549.</mixed-citation></ref></ref-list></back></article>