Implementation reusing the resource blocks allocated to licensed
Implementation of Relay Hopper Model forReliable Communication of IoT Devices in LTEEnvironment through D2D LinkAnish Pradhan, Soumi Basu, Sreetama Sarkar, Saptarshi Mitra and Sanjay Dhar RoyDepartment of Electronics and Communication EngineeringNational Institute of Technology, DurgapurWest Bengal, IndiaAbstract—Internet of things (IoT) is an emerging technologythat can bring about a revolution in our day-to-day lives. Deviceto-device(D2D) communication is an energy and spectral efficientsolution to the growing problem of scarcity of free spectrum andoverloading of base stations in cellular networks. The conceptof using D2D communication in IoT networks has already beenproposed. But the reliability of the links established by reusingthe resource blocks allocated to licensed cellular users has notbeen investigated earlier.
In this paper, our objective is to provideconnectivity between IoT devices and the associated gatewayusing D2D communication ensuring that links established arereliable, and at the same time improve performance by providingconnectivity to the maximum number of IoT devices. We proposea three step approach to achieve this. In the first step, the IoTdevices satisfying the Quality of Service (QoS) constraint areselected and matched with appropriate reuse candidates, that is,the cellular user equipments (CUEs) by an optimum resourceallocation scheme. Next, link reliability of these links are computedand weak links are discarded.
Finally, the disconnected IoTdevices are rerouted to the IoT gateway via IoT devices possessingstrong links following a relay hopper model. Simulation resultsindicate significant improvement in the network performancemetrics, namely, access rate and sum throughput of IoT devices.Index Terms—D2D, IoT, QoS, Resource Allocation, Linkreliability,Relay Hopper ModelI. INTRODUCTIONInternet of things (IoT) is a revolutionary concept where’things’ that have the ability to sense and communicatecollaborate on a network to make important decisions.
In acellular IoT network, there are a number of IoT devices withsensors attached to them. The data collected through thesedevices from the environment are sent to the LTE EvolvedNode B (eNodeB or eNB) via an IoT Gateway (IoT-GW)1.Device to Device (D2D) communication provides a numberof advantages such as higher data rate 2, reduced energyconsumption 34, spectrum efficiency 5 reduced latency6 etc over conventional methods like WiFi, bluetooth etc. Theconcept of using D2D communication to provide connectivitybetween IoT devices and the IoT gateway has been proposedin 5.We have adopted the concept of offloading Machine toMachine (M2M) Communication 7. In this method, a devicelying in poor cell coverage area can establish connection toanother device via a third device (also called offloader or relay)which lies inside the coverage area of the cell in a strategiclocation between two devices intending to connect.We propose a novel three step approach to provide reliablecommunication between the IoT devices and their associatedgateway. In the first step, the IoT devices that satisfy theQuality of Service (QoS) requirement are selected and theseIoT devices are assigned the resources of licensed CUEswhich they can reuse.
We use maximum bipartite matchingas the resource allocation scheme so as to provide service tothe maximum number of IoT devices present in the system.The reliability of the links thus established is investigated inthe next step and the weak links are discarded. Finally, thedisconnected IoT devices are mapped with the ones havingstrong links such that the former acts as a hopper and thelatter as relay to establish connectivity between IoT deviceswith weak links and the IoT gateway. So, the contributions ofthis paper can be summarized as: (a) proposition of a resourceallocation scheme that considers not only QoS requirementbut also reliability of the route 8 between IoT devices andIoT-GW, (b) extension of effective IoT coverage area byintroducing relays, (c) improved network performance withincrease in access rate, sum throughput and average linkreliability of IoT devices.The remaining sections are organized as follows: The systemmodel is discussed in Chapter II. The problem formulationand theoretical analysis of the problem is given in ChapterIII.
Chapter IV posits the Simulation Results and Discussion.Finally, the paper has been concluded in Chapter V.II. SYSTEM MODELThe proposed system model is based on reliable reuse ofuplink resources of CUEs in LTE environment to enable theIoT devices to communicate through the IoT gateway.
In thesimulation environment 5, a cell with several CUEs and aneNodeB at the center is considered. A cluster of IoT deviceswith IoT gateway at its center is introduced in that environmentto facilitate the communication between the IoTs. The IoTgateway acts as the data condenser of all the IoTs and itsends the data to the eNodeB by using the available radioresources from the CUEs.
The whole bandwidth is dividedequally among the CUEs such that they are allocated only oneResource Block (RB) to avoid interference among themselves.Let there be N number of CUE in the cell and they are denotedbyCn|n = 1, 2, 3, …, Nand K number of IoT devices which are represented byIk|k = 1, 2, 3, ..
., KWe have used a distance based exponential path-loss model5Fig. 1: System Modeldescribed asPrx = P0 · (dtx,rx)?a· Ptx (1)where Prx is the received power, Ptx is the transmitted power,P0 is the path-loss constant, dtx,rx is the distance between thetransmitter and the receiver and ‘a’ is the path-loss coefficient.III.
PROBLEM FORMULATION AND THEORETICALANALYSISFollowing 5 we can see, links can be established betweenIoT device and IoT-GW reusing PRBs from CUEs but theauthor did not consider the reliability of links. Here wehave calculated the reliability of the established links withthe method described in 8 and tried to improve them byproposing a relay hopper based system model. We have takena three step approach towards this solution:A. Selection of IoT devices based on QoS requirements5:Due to the constraint that an average fixed value of receivedpower is maintained at eNodeB, the transmission power of nthCUE becomesPCT x(n) = PRx,eNBP0 · (dCn,eNB)?a(2)where n varies from 1 to N, PRx,eNB is the received powerat eNodeB, dCn,eNB = distance between nth CUE device andeNodeB. Interference at eNodeB, InteNB(k) is caused by IoTdevices trying to use the same radio resource of CUE.
To fulfillQoS constraint of CUE, the SIR condition of CUE isPRx,eNBInteNB(k)=P0 · (dCn,eNB)?a· PCT x(n)P0 · (dIk,eNB)?a · PIT x(k)? SIRCn (3)PIT x(k) ?PRx,eNB · (dIk,eNB)aP0 · SIRCn(4)where PIT x(k) is the power transmitted by kth IoT devicethat is using the RB of nth CUE, dIk,eNB is the distancebetween kth IoT device and eNodeB and SIRCn is the targetSIR condition for CUEs. As the maximum transmission powerof the IoT devices are fixed (PImax), the value of PIT x(k)will bePIT x(k) = (PRx,eNB·(dIk,eNB)aP0·SIRCnif dIk,GW ? DnPImax else(5)where Dn is the minimum distance between kth IoT deviceand eNodeB after which the transmit power of the kth IoTdevice reaches its maximum limit.Dn =P0 · PImax · SIRCnPRx,eNB 1/a(6)Similarly, interference at IoT-Gw, IntGW (n) is caused byCUEs whose radio resources are being used by IoT devices.This is given by,PRx,GW (k)IntGW (n)=P0 · (dIk,GW )?a· PIT x(k)P0 · (dCn,GW )?a · PCT x(n)? SIRIk (7)where PRx,GW (k) is received power at IoT-GW, from kthIoT device.
dIk,GW and dCn,GW are distances from IoT-GWto kth IoT Device and nth CUE device respectively. So,PIT x(k) ?PRx,eNB · SIRIk · (dIk,GW )aP0·RatioCnRatioIk !a(8)whereRatioCn =dCn,eNBdCn,GWRatioIk =dIk,eNBdIk,GWLet?(k) = PRx,eNB · SIRIk · (dIk,GW )aP0(9)and? = SIRIk · SIRCn (10)If dIk,GW ? Dn, then from equations (5) and (8) we get,RatioCnRatioIk !a? ? (11)else,RatioCnRatioIk !a? ?(k) (12)Equations (11) and (12) are the necessary conditions to determinewhich IoT device can use the PRB of which reusecandidates and this information is stored. Then matching ofCUE and IoT devices can be done with an optimum resourceallocation scheme. In our case, we have used maximumbipartite matching so that maximum number of CUE-IoTdevice pairing is possible that will contribute in improvedaccess rate of the system.B. Elimination of IoT devices with weak links:After initial pairing of CUE and IoT devices, we calculatethe reliability of the links between paired IoT devices andIoT-GW 8 by the following equation.RelIk = exp?(dIk,GW )aSINRGW (k)(13)where,SINRGW (k) = PIT x(k)NT + Interference from respective CUEsand NT = Thermal Noise. This reliability is defined as theprobability of successful transmission over the given route8.
We have assumed transmit power of each IoT devicesas their maximum transmit power (PImax) considering thecomplexity of calculations and its almost negligible impacton the results. After calculation of the reliabilities of thosedirect links from IoT devices to IoT-GW, we discard theweaker links by thresholding them against a minimum fixedprobability value (Relth). Now, we have a number of IoTdevices which have direct strong links to the IoT-GW anda handful of remaining IoT devices which satisfy the QoSconstraints and were paired with CUEs by bipartite matchingbut can not provide reliable transmission of data as per therequirement of real time environment. Discarding weak links,on one hand, abates wastage of resources, but on the otherhand, access rate potentially decreases. We can further increaseaccess rate by introducing a relay-hopper system as discussedin the next section.
C. Rerouting the eliminated IoT devices by choosing relayhopperpairWith the help of a link threshold value based on distance betweenconnected and disconnected IoT devices with ability toaccess PRB, a new link can be established between them wherethe previously disconnected IoT device named as hopper canconnect to IoT-GW through one of the previously connectedIoT devices named as relay with reliable link strength. So thenew link reliability between a probable hopper candidate k3and IoT-GW through a probable relay candidate k2 can becalculated as,RelIk3,Ik2 = exp?(dIk2,GW )aSINRGW (k3)?(dIk2,IK3)aSINRGW (k3)!(14)The information about all the remaining and discarded IoTdevices is stored. If the total link reliability of any of thisrelay-hopper pair exceeds a threshold value (Relth), then theybecome eligible for being a relay or a hopper. After that, weused bipartite matching to yield maximum number of relayhopperpairs. This proposed system can increase access rateas more reliable links are established. The trade off done hereis link sharing between two IoT devices, which do not imposeserious threat as the IoT devices do not require an entire PRBfor their communication as found from data.IV.
SIMULATION RESULTS AND OBSERVATIONWe simulated the proposed model described in sectionII in MATLAB. Access rate, average link reliability, sumthroughput of IoT devices are used as the performance metricsto evaluate the system. Access rate is the ratio of numberof allocated IoT devices to the total number of IoT deviceswhereas sum throughput is the aggregate of throughputs of allthe allocated IoT devices and average link reliability is averagevalue of reliability of all the existing links between connectedIoT devices and IoT-GW.Average link reliability =1K1XK1k=1RelIk (15)Sum Throughput =XK1k=1XN1n=1log21 +PRx,GW (k)NT + IntGW (n)!(16)where N1 = Number of reuse CUE candidates, K1 = Numberof resource allocated IoT devices.
As IoT devices transmit datausually at a small amount for some limited slot of time 9,the effect of adding a hopper on calculating the throughputof that relay IoT device is not considered here. Our proposedscheme is compared with the scheme discussed here 5.Fig. 2: Access Rate vs number of IoT devices before and afterintroducing Relay-Hopper mechanism where dIoTD,GW =150m, dGW,eNB = 500mFrom Fig.2 and Fig.
3, we can see the improvement ofAccess rate and sum throughput with the relay-hopper model.It is observed that the improvement increases with increasein number of IoT devices. Fig.4 shows that average linkreliability is improved significantly after implementing relayhoppermodel.Fig. 3: Sum throughput vs number of IoT devices beforeand after introducing Relay-Hopper mechanism wheredIoTD,GW = 150m, dGW,eNB = 500mFig. 4: Average link reliability vs number of IoT devicesbefore and after introducing Relay-Hopper mechanism wheredIoTD,GW = 150m, dGW,eNB = 500mV. CONLUSION AND FUTURE WORKIn this paper, we have studied a new method of interconnectingIoT devices using a two-hop scheme on deviceto device communication technology in LTE environmentusing the spectrum more efficiently.
We have calculated thelink strength between IoT devices and Gateway to tackle theproblem of bad links by implementing Relay-Hopper pairs.In device to device communication of IoT devices, the linkreliability parameter has not been considered before but thatis of paramount importance in real time data traffic. Theincrement of sum throughput of IoT devices after introducingRelay-Hopper pairs has also been illustrated. In future, thiswork can be extended by considering more than two hopsand finding out the optimum solution by examining the tradeoff between number of hops and performance improvement.Considering mobility of the devices and incorporating approTABLEI: Simulation Parameters 5Parameters ValueUplink System Bandwidth 100 MHzNumber of RBs 500Bandwidth of each RB 180 KHzNumber of CUEs(N) 500Number of IoTDs(K) 1-100% of CUEsCell Radius 1000 mSIRCn 25 dBSIRIk 20 dBPath loss exponent, a 4P0 10?2Noise Power Spectral Density -174 dBm/HzPImax 23 dBmLink reliability threshold, Relth 0.5priate power control scheme may also be introduced for bettersystem efficiency.