Hybrid Access Control Mechanism in Two-Tier Femtocell Networks

The cellular industry is undergoing a major paradigm shift from voice-centric, structured homogeneous networks to a more data-driven, distributed and heterogeneous architecture. One of the more promising trends emerging from this cellular revolution is femtocells. Femtocells are primarily viewed as a cost-effective way to improve both capacity and indoor coverage, and they enable offloading data-traffic from macrocell network. However, efficient interference management in co-channel deployment of femtocells remains a challenge. Decentralized strategies such as femtocell access control have been identified as an effective means to mitigate cross-tier interference in two-tier networks. Femtocells can be configured to be either open access or closed access. Prior work on access control schemes show that, in the absence of any coordination between the two tiers in terms of power control and user scheduling, closed access is the preferred approach at high user densities. Present methods suggest that in the case of orthogonal multiple access schemes like TDMA/OFDMA, femtocell access control should be adaptive according to the estimated cellular user density. The approach we follow, in this work, is to adopt an open access policy at the femtocell access points with a cap on the maximum number of users allowed on a femtocell. This ensures the femto owner retains a significant portion of the femtocell resources. We design an iterative algorithm for hybrid access control for femtocells that integrates the problems of uplink power control and base station assignment. This algorithm implicitly adapts the femtocell access method to the current user density. The distributed power control algorithm, which is based on Yates' work on standard interference functions, enables users to overcome the interference in the system and satisfy their minimum QoS requirements. The optimal allocation of femtocell resources is incorporated into the access control algorithm through a constrained sum-rate maximization to protect the femto owner from starvation at high user densities. The performance of a two-tier OFDMA femtocell network is then evaluated under the proposed access scheme from a home owner viewpoint, and network operator perspective. System-level simulations show that the proposed access control method can provide a rate gain of nearly 52% for cellular users, compared to closed access, at high user densities and under moderate-to-dense deployment of femtocells. At the same time, the femto owner is prevented from going into outage and only experiences a negligible rate loss. The results obtained establish the quantitative performance advantage of using hybrid access at femtocells with power control at high user densities. The convergence properties of the proposed iterative hybrid access control algorithm are also investigated by varying the user density and the mean number of femto access points in the network. It is shown that for a given system model, the algorithm converges quickly within thirty iterations, provided a feasible solution exists

Improving power and resource management in heterogeneous downlink OFDMA networks

© 2020 by the authors. In the past decade, low power consumption schemes have undergone degraded communication performance, where they fail to maintain the trade-off between the resource and power consumption. In this paper, management of resource and power consumption on small cell orthogonal frequency-division multiple access (OFDMA) networks is enacted using the sleep mode selection method. The sleep mode selection method uses both power and resource management, where the former is responsible for a heterogeneous network, and the latter is managed using a deactivation algorithm. Further, to improve the communication performance during sleep mode selection, a semi-Markov sleep mode selection decision-making process is developed. Spectrum reuse maximization is achieved using a small cell deactivation strategy that potentially identifies and eliminates the sleep mode cells. The performance of this hybrid technique is evaluated and compared against benchmark techniques. The results demonstrate that the proposed hybrid performance model shows effective power and resource management with reduced computational cost compared with benchmark techniques

EMB: Efficient Multimedia Broadcast in Multi-tier Mobile Networks

Multimedia broadcast and multicast services (MBMS) in mobile networks has been widely addressed, however an investigation of such a technology in emerging, multi-tier, scenarios is still lacking. Notably, user clustering and resource allocation are extremely challenging in multi-tier networks, and imperative to maximize system capacity and improve quality of user-experience (QoE) in MBMS. Thus, in this paper we propose a clustering and resource allocation approach, named EMB, which specifically addresses heterogeneous networks and accounts for the fact that multimedia content is adaptively encoded into scalable layers depending on the QoE requirements and channel conditions of the heterogeneous users. Importantly, we prove that our clustering algorithm yields Pareto efficient broadcasting areas, multimedia encoding parameters, and re- source allocation, in a way that is also fair to the users. Fur- thermore, numerical results obtained under realistic conditions and using real-world video content, show that the proposed EMB results in lower churn count (i.e., higher number of served users), higher throughput, and increased QoE, while using fewer network resources