With increase in demand of data traffic with no compromise on the underlying quality of service (QoS), the coexistence problem arises due to high electricity consumption by the network architecture which results in a huge CO2 emission and thereby causing various health hazards. Efficient utilization of the resources can reduce the cost of power consumption which will increase the economy-characteristics of the network. The resource consumption can be reduced under an intelligent technology-neutral policies which optimizes the deployment of the network architecture along with their transmit power paving the way for fifth generation (5G) in green wireless communications. On another front, the ultra-dense deployment of the small cells can increase the frequency reuse factor as well as help in reducing the energy consumption. This chapter designs the energy efficient networks while satisfying the underlying QoS by joint optimization of available resources depending on the interoperability challenges in terrestrial, underwater acoustic, and free space optical (FSO) communications.
TopIntroduction
This chapter describes a quality-of-service (QoS)-aware energy-efficient network in terrestrial, underwater acoustic and free space optical (FSO) communications according to the interoperability challenges in their transmission links as shown in Figure 1.
The demand of data is increasing day by day without any compromise with QoS. For improving the coverage of the user equipments (UEs), various works have been done on the deployment of base stations (BSs) in cellular networks. Deployment in grid-based network where the shape of the cells is hexagonal is less tractable (ElSawy, Hossain & Haenggi, 2013). Placement of BSs based on homogeneous Poisson point process (HPPP) and binomial point process (BPP) is realistic (Andrews, Baccelli & Ganti, 2011; Srinivasa & Haenggi, 2010), but deterministic deployment of BSs using the distribution of UEs gives significant performance enhancement (Su et al, 2014). The power consumption in the cellular network is nearly 1% of the world wide total energy consumption (Fettweis, & Zimmermann, 2008). Therefore, it leads to a need for an energy-efficient network design for minimizing the operational cost of the network while satisfying the quality-of-service (QoS) of the network.
Also, the energy-efficient network design in underwater acoustic networks (UANs) has gained significant research interest in recent years (Darehshoorzadeh & Boukerche, 2015). As the underwater acoustic channel has large delay and restricted bandwidth in long-range communications. Therefore, for satisfying a minimum data rate, it is required to transmit the signal through a relay in a cooperative communication by reducing the hop length which also gives an energy-efficient design (Stojanovic, 2007). Thus, this chapter investigates the green network by jointly optimizing the power allocation (PA) and relay placement (RP) in a dual-hop UAN where the direct link is absent.
Figure 1. Optimal resource allocation in cooperative underwater acoustic, FSO, and terrestrial networks while tackling the underlying interoperability challenges
As the optical communication in wireless channel is an alternative of fulfilment of demand of high data rate with less power consumption in congested radio frequency (RF) spectrum, this has enforced a research interest in free space optical (FSO) communication. The usage of FSO communication ranges from home network to satellite communication (Son, & Mao, 2017). However, the range of FSO communication is limited by lots channel impairments due to atmospheric turbulence, pointing error, and angle-of-arrival (AOA) fluctuations (Huang, & Safari, 2017). Again, using relay-assisted cooperative communication, the link length can be reduced which is also helpful in reducing the channel impairments in FSO communications (Saidi, Tourki, & Hamdi, 2016).
TopBackground
From the state-of-the-art, most of the works have deployed the BSs and UEs according to HPPP. Andrews et al. (2011) have evaluated that HPPP is more tractable than conventional grid method for the deployment. But it has been shown that BPP is more tractable than HPPP with respect to distribution of points and size of the network (Srinivasa & Haenggi, 2010). Placement of BSs based on homogeneous Poisson point process (HPPP) and binomial point process (BPP) is realistic (Andrews, Baccelli & Ganti, 2011; Srinivasa & Haenggi, 2010), but deterministic deployment of BSs using the distribution of UEs gives significant performance enhancement (Su et al, 2014). Therefore, in the energy-efficient network design, the BSs are deterministically deployed according to the distribution of UEs by BPP.