Cooperative and coordinated Mobile Femtocells technology in high-speed vehicular environments: mobility and interference management

In future networks, most users who will be accessing wireless broadband will be vehicular. Serving those users cost-effectively and improving their signal quality has been the main concern of many studies. Thus, the deployment of Mobile Femtocell (Mobile-Femto) technology on public transportation is seen to be one of the promising solutions. Mobile-Femto comes with its mobility and interference challenges. Therefore, eliminating the Vehicular Penetration Loss (VPL) and interference while improving signal quality and mobility for train passengers is the main concern of this paper. The initial system-level evaluation showed that the dedicated Mobile-Femto deployment has great potential in improving users’ experience inside public transportation. The Downlink (DL) results of the Proposed Interference Management Scheme (PIMS) showed significant improvement in Mobile-Femto User Equipment (UE) gains (up to 50%) without impacting the performance of macro UEs. In contrast, the Uplink (UL) results showed noticeable gains for both macro UEs and Mobile-Femto UEs

Interference management and system optimisation for Femtocells technology in LTE and future 4G/5G networks

Femtocells are seen to be the future of Long Term Evaluation (LTE) networks to improve the performance of indoor, outdoor and cell edge User Equipments (UEs). These small cells work efficiently in areas that suffer from high penetration loss and path-loss to improve the coverage area. It is said that 30% of total served UEs in LTE networks are vehicular, which poses challenges in LTE networks due to their high mobility, high vehicular penetration loss (VPL), high path loss and high interference. Therefore, self-optimising and dynamic solutions are required to incorporate more intelligence into the current standard of LTE system. This makes the network more adaptive, able to handle peak data demands and cope with the increasing capacity for vehicular UEs. This research has drawn a performance comparison between vehicular UEs who are served by Mobile-Femto, Fixed-Femto and eNB under different VPL scales that range between highs and lows e.g. 0dB, 25dB and 40dB. Deploying Mobile-Femto under high VPLs has improved the vehicular UE Ergodic capacity by 1% and 5% under 25dB and 40dB VPL respectively as compared to other eNB technologies. A noticeable improvement is also seen in signal strength, throughput and spectral efficiency. Furthermore, this research discusses the co-channel interference between the eNB and the Mobile-Femto as both share the same resources and bandwidth. This has created an interference issue from the downlink signals of each other to their UEs. There were no previous solutions that worked efficiently in cases where UEs and base stations are mobile. Therefore, this research has adapted an efficient frequency reuse scheme that worked dynamically over distance and achieved improved results in the signal strength and throughput of Macro and Mobile-Femto UE as compared to previous interference management schemes e.g. Fractional Frequency Reuse factor1 (NoFFR-3) and Fractional Frequency Reuse factor3 (FFR-3). Also, the achieved results show that implementing the proposed handover scheme together with the Mobile-Femto deployment has reduced the dropped calls probability by 7% and the blocked calls probability by 14% compared to the direct transmission from the eNB. Furthermore, the outage signal probabilities under different VPLs have been reduced by 1.8% and 2% when the VPLs are 25dB and 40dB respectively compared to other eNB technologies

Femtocell Coverage Optimisation Using Statistical Verification

Part 7: Network Topology ConfigurationInternational audienceFemtocells are small base stations that provide radio coverage for mobile devices in homes or office areas. In this paper, we consider the optimisation of a number of femtocells that provide joint coverage in enterprise environments. In such an environment, femtocells should minimise coverage overlap and coverage holes and ensure a balanced traffic workload among them. We use statistical verification techniques to monitor the probabilistic correctness of a given femtocell configuration at runtime. If there is any violation of the desired level of service, a self-optimisation procedure is triggered to improve the current configuration. Our evaluation results show that, compared with fixed time, interval-based optimisation, our approach achieves better coverage and can detect goal violations quickly with a given level of confidence when they occur frequently. It can also avoid unnecessary self-optimisation cycles, reducing the cost of self-optimisation