**5. Simulation model**

An OMNET++ version 5.1.1-based simulation model is developed utilizing the SimuLTE library [32] that utilizes the INET framework 3.4.0. For enhanced traffic simulation, GPS data incorporation, and mobility support, we utilized the Veins Package with a realistic mobility model generated by the microscopic road traffic simulation package: Simulation of Urban Mobility (SUMO) [33]. To add the mobility support feature in SimuLTE, a new interface known as vehicularMobility module has been added. This new mobility model can be implemented by the TraCIMobility module defined by the Veins. There is another mobility module known as INETMobility present in the INET framework. A vehicle can utilize only one mobility module during the simulation; therefore both modules (i.e., INETMobility and vehicularMobility) are defined as a conditional module within the Ned file. Veins use the OMNeT++ API to create and initialize the new module dynamically. When a new vehicle is created, it needs to obtain an IP address to communicate. SimuLTE demands the assignment of IP addresses to the IPv4NetworkConfigurator module provided by INET.

A new parameter, i.e., d2dcapable, is utilized in the .ini file to enable direct communication between two UEs. Most of the PC-5 operations at each layer of the LTE stack are created by extending pre-existing SimuLTE capacities. For each D2D competent user, an LTE binder keeps up a data structure that contains the set of directly reachable destinations. In expansion to the existing DL/UL ones in SimuLTE, a new flow path, PC-5, has been distinguished. From the UE point of view, IP datagrams reach the PDCP layer and either the PC-5 or the UL directions can be associated with the corresponding flow, depending on whether the destination is in the LTE Binder peering table or not. The detailed description of configuring D2D communication in OMNET++ with SimuLTE is given in [34]. The key simulation parameters are summarized in **Table 4**.

We modified the existing D2D communication model in the SimuLTE to support our proposed cluster-based cellular V2V architecture. **Figure 13** shows the CBC-V2V communication model consists of an access network entity (single eNodeB) and core network entities (MME, HSS, and GMLS) are utilized to support our proposed EPC Level Sidelink Peer Discovery model. In the simulation, we design a multilane highway scenario where the vehicles are distributed according to the Poisson process. The vehicles form the clusters using our proposed clustering scheme for D2D communication. To implement our proposed clustering scheme, we utilize the sample source code accessible online [35]. Each cluster node keeps up neighborhood table that contains its neighbor's ID and their state. In the simulation, we include scenarios of both multicast and unicast shown in **Figure 12**. The model is simulated for both scenarios utilizing the parameters presented in **Table 4** for 800 seconds. At the MAC layer in the SimuLTE, we modified the scheduling model (i.e., LTEDrr) to implement our proposed round-robin scheduling scheme presented in Section 4. Utilizing the proposed round-robin scheduling technique, each cluster node receives an equal share of the radio resource for D2D communication.

signaling overhead, and data packet delivery ratio performance of our cluster-based D2D vehicular network architecture. The following performance metrics are used to

**Parameter Value** Maximum velocity 40–70 km/h Number of vehicles 96 vehicles/km

*DOI: http://dx.doi.org/10.5772/intechopen.91948*

*An LTE-Direct-Based Communication System for Safety Services in Vehicular Networks*

Carrier frequency 2.6 GHz Duplexing mode TDD CAM generation rate 10 packets/sec Transmission bandwidth 3 MHz (i.e., 15 RBs) Path loss model Highway scenario Fading model Shadowing eNodeB Tx power 46 dBm

Coverage range 1000 m Noise figure 5 dB Cable loss 2 dB Simulation time 800 s Packet size 340 bytes *T*safety 100 ms Number of vehicle/cluster 12 *CH*maxmember 11

Road length and number of lanes 5 km and 4 (i.e., 2 in each direction)

UE Tx Power 26 dBm (Uplink), 5 dBm (Sidelink)

The signaling overhead is measured for the proposed EPC level peer discovery and the D2D packet communication techniques. The overall signaling overhead of

evaluate the proposed algorithm.

*5.1.1 Control signaling overhead*

**Table 4.**

**Figure 13.**

**117**

*CBC-V2V simulation model.*

*Main simulation parameters.*

the network can be calculated as

#### **5.1 Performance analysis**

Using the number of clusters/km and the traffic load (i.e., number of vehicles/ cluster) parameters, we examine the overall end-to-end delay, resource utilization, *An LTE-Direct-Based Communication System for Safety Services in Vehicular Networks DOI: http://dx.doi.org/10.5772/intechopen.91948*


#### **Table 4.**

concerned neighbor *CHB*<sup>0</sup> over the LTE interface. The *CHB*<sup>0</sup> multicasts the safety message to its cluster members *VB1* and *VB2* via the LTE-D2D PC5 interface.

*Moving Broadband Mobile Communications Forward - Intelligent Technologies for 5G…*

An OMNET++ version 5.1.1-based simulation model is developed utilizing the SimuLTE library [32] that utilizes the INET framework 3.4.0. For enhanced traffic simulation, GPS data incorporation, and mobility support, we utilized the Veins Package with a realistic mobility model generated by the microscopic road traffic simulation package: Simulation of Urban Mobility (SUMO) [33]. To add the mobility support feature in SimuLTE, a new interface known as vehicularMobility mod-

ule has been added. This new mobility model can be implemented by the TraCIMobility module defined by the Veins. There is another mobility module known as INETMobility present in the INET framework. A vehicle can utilize only

one mobility module during the simulation; therefore both modules (i.e.,

communicate. SimuLTE demands the assignment of IP addresses to the

IPv4NetworkConfigurator module provided by INET.

simulation parameters are summarized in **Table 4**.

of the radio resource for D2D communication.

**5.1 Performance analysis**

**116**

INETMobility and vehicularMobility) are defined as a conditional module within the Ned file. Veins use the OMNeT++ API to create and initialize the new module dynamically. When a new vehicle is created, it needs to obtain an IP address to

A new parameter, i.e., d2dcapable, is utilized in the .ini file to enable direct communication between two UEs. Most of the PC-5 operations at each layer of the LTE stack are created by extending pre-existing SimuLTE capacities. For each D2D competent user, an LTE binder keeps up a data structure that contains the set of directly reachable destinations. In expansion to the existing DL/UL ones in SimuLTE, a new flow path, PC-5, has been distinguished. From the UE point of view, IP datagrams reach the PDCP layer and either the PC-5 or the UL directions can be associated with the corresponding flow, depending on whether the destination is in the LTE Binder peering table or not. The detailed description of configuring D2D communication in OMNET++ with SimuLTE is given in [34]. The key

We modified the existing D2D communication model in the SimuLTE to support our proposed cluster-based cellular V2V architecture. **Figure 13** shows the CBC-V2V communication model consists of an access network entity (single eNodeB) and core network entities (MME, HSS, and GMLS) are utilized to support our proposed EPC Level Sidelink Peer Discovery model. In the simulation, we design a multilane highway scenario where the vehicles are distributed according to the Poisson process. The vehicles form the clusters using our proposed clustering scheme for D2D communication. To implement our proposed clustering scheme, we utilize the sample source code accessible online [35]. Each cluster node keeps up neighborhood table that contains its neighbor's ID and their state. In the simulation, we include scenarios of both multicast and unicast shown in **Figure 12**. The model is simulated for both scenarios utilizing the parameters presented in **Table 4** for 800 seconds. At the MAC layer in the SimuLTE, we modified the scheduling model (i.e., LTEDrr) to implement our proposed round-robin scheduling scheme presented in Section 4. Utilizing the proposed round-robin scheduling technique, each cluster node receives an equal share

Using the number of clusters/km and the traffic load (i.e., number of vehicles/ cluster) parameters, we examine the overall end-to-end delay, resource utilization,

**5. Simulation model**

*Main simulation parameters.*

**Figure 13.** *CBC-V2V simulation model.*

signaling overhead, and data packet delivery ratio performance of our cluster-based D2D vehicular network architecture. The following performance metrics are used to evaluate the proposed algorithm.

### *5.1.1 Control signaling overhead*

The signaling overhead is measured for the proposed EPC level peer discovery and the D2D packet communication techniques. The overall signaling overhead of the network can be calculated as

*Moving Broadband Mobile Communications Forward - Intelligent Technologies for 5G…*

$$X\_{SO}(\mathcal{c}) = \sum\_{i \in N} (\overline{\mathbf{x}}\_{pd} + \overline{\mathbf{x}}\_{d2d}) \tag{1}$$

where *xpd* represents the average signaling overhead in bits related to the control signaling required for the peer discovery and *xd*2*<sup>d</sup>* represents the average signaling overhead related to the control signaling required for the D2D communication. *xpd* can be calculated as the number of slots used for peer discovery out of the total number of *n* subframe available in the cell *i* as

$$\overline{\mathfrak{X}}\_{pd} = \frac{\mathfrak{X}\_{\dot{r}1} + \mathfrak{X}\_{\dot{r}2} + \mathfrak{X}\_{\dot{r}3}, \dots, \mathfrak{X}\_{\dot{r}m}}{n} \times 100 \tag{2}$$

Similarly, we calculate *xd*2*<sup>d</sup>* the overhead for the D2D communication and calculate the overall signaling overhead. **Figure 14** shows the signaling overhead required by the CBC-V2V, the default 3GPP ProSe algorithm, and the LTE-Advanced algorithm using conventional cellular architecture. The results clearly show that the CBC-V2V introduces lower signaling overhead compared to the other two standards which can be used in a VANET. The main reason for the performance improvement is the lower control signaling requirement for the CBC-V2V algorithm. The major benefit comes from our ESPD algorithm which requires less control message exchange for peer discovery compared to existing peer discovery models described in Section 4. Unlike the existing 3GPP peer discovery model, in the ESPD algorithm, a vehicle receives the proximity information after the successful registration which requires very less control message exchange as shown in **Figure 2**. The smaller control signaling overhead requirement will improve the performance of safety services and guarantee the timely delivery of active safety messages.

**Figure 15** shows the overall resource utilization of the CBC-V2V algorithm for safety services. We compare the results with the standard ProSe solutions in terms of a number of occupied RBs. The efficient scheduler minimizes resource utilization and distribution levels. In the CBC-V2V, each of the CH acts as a scheduler and distributes the resources among its CMs using our proposed round-robin scheduling. Two clusters can be served in a single subframe, and nonoverlapping clusters can share the same resource. Resource utilisation of the CBC-V2V algorithm is lower compared to 3GPP ProSe algorithm due to lower control signal requirements, cluster architecture and efficient resource allocation technique of the algorithm.

**Figure 16** shows DPDR of the CBC-V2V and compares it with two existing standard procedures. The DPDR is characterized as the proportion of the total number of received safety packets to the total number of scheduled safety packets. Due to the closer vicinity of vehicles, the DPDR value increases with the number of clusters. The system based on IEEE 802.11p shows the lowest DPDR value because packets are lost due to collisions then the proposed D2D packet communication technique which is contention-free. Subsequently, the packet loss probability is low,

**12345678 Number of clusters/km**

*An LTE-Direct-Based Communication System for Safety Services in Vehicular Networks*

The total end-to-end delay (*δ<sup>E</sup>*2*<sup>E</sup>*) for a transmission of a safety message consists

where *δPD* represents the total delay in peer discovery, which is the time difference between sending a request for registration and receiving an eNodeB response and *δ<sup>D</sup>*2*<sup>D</sup>* represents the total delay in D2D packet communication, which is the sum

*δ<sup>E</sup>*2*<sup>E</sup>* ¼ *δPD* þ *δ<sup>D</sup>*2*<sup>D</sup>* (3)

**CBC-V2V (Multicast) CBC-V2V (Unicast) 3GPP ProSe communication**

**IEEE 802.11p**

due to transmission channel condition.

*Performance comparison in terms of data packet delivery ratio.*

*Performance comparison in terms of total occupied RBs.*

*DOI: http://dx.doi.org/10.5772/intechopen.91948*

of two major delay components as

*5.1.2 Total end-to-end delay*

**Data Packet Delivery Ratio (%)**

**Figure 15.**

**Figure 16.**

**119**

**Figure 14.** *Performance comparison in terms of signaling overhead.*

*An LTE-Direct-Based Communication System for Safety Services in Vehicular Networks DOI: http://dx.doi.org/10.5772/intechopen.91948*

**Figure 15.** *Performance comparison in terms of total occupied RBs.*

*XSO*ð Þ¼ *<sup>c</sup>* <sup>X</sup>

*Moving Broadband Mobile Communications Forward - Intelligent Technologies for 5G…*

number of *n* subframe available in the cell *i* as

messages.

**Figure 14.**

**118**

**Signalling Overhead (%)**

**CBC-V2V**

*Performance comparison in terms of signaling overhead.*

**3GPP ProSe communication (without clustering)**

**LTE-Advnaced (with clustering)**

*i* ∈ *N*

*xpd* <sup>¼</sup> *xir*<sup>1</sup> <sup>þ</sup> *xir*<sup>2</sup> <sup>þ</sup> *xir*3, … , *xirn n*

Similarly, we calculate *xd*2*<sup>d</sup>* the overhead for the D2D communication and calculate the overall signaling overhead. **Figure 14** shows the signaling overhead required by the CBC-V2V, the default 3GPP ProSe algorithm, and the LTE-Advanced algorithm using conventional cellular architecture. The results clearly show that the CBC-V2V introduces lower signaling overhead compared to the other two standards which can be used in a VANET. The main reason for the performance improvement is the lower control signaling requirement for the CBC-V2V algorithm. The major benefit comes from our ESPD algorithm which requires less control message exchange for peer discovery compared to existing peer discovery models described in Section 4. Unlike the existing 3GPP peer discovery model, in the ESPD algorithm, a vehicle receives the proximity information after the successful registration which requires very less control message exchange as shown in **Figure 2**. The smaller control signaling overhead requirement will improve the performance of safety services and guarantee the timely delivery of active safety

**Figure 15** shows the overall resource utilization of the CBC-V2V algorithm for safety services. We compare the results with the standard ProSe solutions in terms of a number of occupied RBs. The efficient scheduler minimizes resource utilization and distribution levels. In the CBC-V2V, each of the CH acts as a scheduler and distributes the resources among its CMs using our proposed round-robin scheduling. Two clusters can be served in a single subframe, and nonoverlapping clusters can share the same resource. Resource utilisation of the CBC-V2V algorithm is lower compared to 3GPP ProSe algorithm due to lower control signal requirements, cluster architecture and efficient resource allocation technique of the algorithm.

> **12345678 Number of clusters/km**

where *xpd* represents the average signaling overhead in bits related to the control signaling required for the peer discovery and *xd*2*<sup>d</sup>* represents the average signaling overhead related to the control signaling required for the D2D communication. *xpd* can be calculated as the number of slots used for peer discovery out of the total

*xpd* þ *xd*2*<sup>d</sup>*

� � (1)

� 100 (2)

**Figure 16.** *Performance comparison in terms of data packet delivery ratio.*

**Figure 16** shows DPDR of the CBC-V2V and compares it with two existing standard procedures. The DPDR is characterized as the proportion of the total number of received safety packets to the total number of scheduled safety packets. Due to the closer vicinity of vehicles, the DPDR value increases with the number of clusters. The system based on IEEE 802.11p shows the lowest DPDR value because packets are lost due to collisions then the proposed D2D packet communication technique which is contention-free. Subsequently, the packet loss probability is low, due to transmission channel condition.

#### *5.1.2 Total end-to-end delay*

The total end-to-end delay (*δ<sup>E</sup>*2*<sup>E</sup>*) for a transmission of a safety message consists of two major delay components as

$$
\delta\_{\rm E2E} = \delta\_{\rm PD} + \delta\_{\rm D2D} \tag{3}
$$

where *δPD* represents the total delay in peer discovery, which is the time difference between sending a request for registration and receiving an eNodeB response and *δ<sup>D</sup>*2*<sup>D</sup>* represents the total delay in D2D packet communication, which is the sum of the intra- and inter-cluster delays in communication. To ensure timely delivery of active safety messages, the total end-to-end delay (i.e., *δE*2*E*) of the safety message should be less than the required delivery delay (i.e., *Tsafety*).

**6. Conclusion**

conditions.

**Abbreviations**

VANET vehicular ad hoc network ITS intelligent transportation system

*DOI: http://dx.doi.org/10.5772/intechopen.91948*

DENM decentralized environmental notification messages

CSMA/CA carrier-sense multiple access with collision avoidance

E-UTRAN Enhanced UMTS Terrestrial Radio Access Network

ESPD evolved packet core level sidelink peer discovery

SC-FDMA single-carrier frequency division multiple access

V2V vehicle-to-vehicle V2N vehicle-to-network V2P vehicle-to-pedestrian V2I vehicle-to-infrastructure V2X vehicle-to-everything RV remote vehicle HV host vehicle RSU road side unit

STCH SL traffic channel

ProSe proximity service

UE user equipment

EPC evolved packet core

eNB eNodeB

**121**

DPDR data packet delivery ratio

SPS semi-persistent scheduling LTE long term evolution

CAM cooperative awareness message

CBC-V2V cluster-based cellular vehicle-to-vehicle

CACC cooperative adaptive cruise control

GNSS global navigation satellite system

EPUID EPC ProSe subscriber ID ALUID application layer user ID PSS primary synchronization signal

SBBCH SL Broadcast Control Channel SCI SL control information PSSH physical SL shared channel

PSDCH physical sidelink discovery channel

This chapter has introduced an advanced new cluster-based V2V packet communication architecture combined with an EPC level peer discovery model suitable for vehicular safety applications. The ESPD model reduces the control signaling overhead and end-to-end delay with the awareness of proximity utilizing the GPS information. The CBC-V2V also combines a cluster-based round-robin scheduling technique to distribute the radio resource among the cluster nodes. The CBC-V2V can improve resource utilization and reduce the end-to-end delay to meet the QoS requirements of the safety services in VANETs. Simulation results show that the CBC-V2V offers higher QoS than do the IEEE 802.11p and other LTE networking architectures. The research will be further extended to examine the vehicular network performance in different road terrains and transmission

*An LTE-Direct-Based Communication System for Safety Services in Vehicular Networks*

**Figures 17** and **18** present the delay analysis of the CBC-V2V algorithm as a function of the total number of clusters formed based on the number of vehicles/ km. **Figure 17** evaluates and compares the peer discovery delay of the ESPD with the 3GPP ProSe peer discovery model described in Section 4. In the proposed ESPD, the peer discovery delay is the time taken by each vehicle for successful registration. In the registration response, each vehicle receives its current traffic profile which contains the list directly reachable vehicle in its vicinity. Due to the less resource utilization and minimal control signaling overhead requirement, ESPD shows the lower delay values for the peer discovery task compared to the existing 3GPP ProSe peer discovery model. **Figure 18** shows the overall end-to-end packet delay of the CBC-V2V. The results show that the CBC-V2V outperforms the traditional approaches such as IEEE 802.11p, LTE-D2D, and LTE for the safety message transmission in a VANET.

**Figure 17.** *Performance comparison in terms of peer discovery delay.*

**Figure 18.** *Performance comparison in terms of E2E packet delay.*

*An LTE-Direct-Based Communication System for Safety Services in Vehicular Networks DOI: http://dx.doi.org/10.5772/intechopen.91948*
