Performance Evaluation for Wi-Fi Offloading Schemes in LTE Networks

Abstract

The exponential data traffic growth cannot be satisfied anymore with traditional ways by building new Base Stations (BS) or leasing new spectrum bands, which is costly from the operator's point of view. In order to accommodate with this high data proliferation, the Third Generation Partner Ship Project (3GPP) has introduced Long Term Evolution (LTE). An LTE network can handle more traffic with reduced cost and complexity, by adding new spectrum and wider bands. Researchers are more interested in coping with increased capacity by involving a heterogeneous network along with LTE as a better solution. The focus of this research is to discuss a specific variation of heterogeneous networks, which is Multi Radio Access Technology (RAT), as multiple

Adaptive Wi-Fi offloading schemes in heterogeneous networks, the survey

“…Table 1 provides the 3 factors most used to determine NSS. In his research [30]- [33], implemented "Wi-Fi First" which is a network selection scheme (NSS) based on received signal strength (RSS). When users of an long-term evolution (LTE) network are switched to a Wi-Fi network, the capacity of the LTE network is only reduced by 2.75%.…”

“…In HHO, the work system adheres to the highest RSS value, while in VHO it optimizes the resources between radio access networks. For this reason, researchers are currently making efforts to optimize the performance of heterogeneous networks [30], [36]. They combine the concept of genetic zone routing protocol (GZRP) with the VHO Algorithm to be applied to BTS networks.…”

“…Energy-aware device-oriented adaptation scheme For a higher level, the optimizer handles load balancing and application placement issues towards maximizing the number of offload requests. In contrast to traditional techniques that apply computational offload to a single server, the parallel offload method can improve system performance [30]. Static application component multi-partition algorithm is difficult to maintain optimality, this is due to the variability of the communication and computing environment according to the time-varying scenario.…”