Search

With the proliferation of mobile terminals and the continuous upgrading of services, 4G LTE networks are showing signs of weakness. To enhance the capacity of wireless networks, millimeter waves are introduced to drive the evolution of networks towards multi-band 5G heterogeneous networks. The distinct propagation characteristics of mmWaves and microwaves, as well as the vastly different hardware configurations of heterogeneous base stations, make traditional access strategies no longer effective. Therefore, to narrowing the gap between theory and practice, we investigate the access strategy in multi-band 5G heterogeneous networks, taking into account the characteristics of mobile users, asynchronous switching between uplink and downlink of pico base stations, asymmetric service requirements, and user communication continuity. We formulate the problem as integer nonlinear programming and prove its intractability. Thereby, we decouple it into three subproblems: user association, switch point selection, and subchannel allocation, and design an algorithm based on optimal matching and spectral clustering to solve it efficiently. The simulation results show that the proposed algorithm outperforms the comparison methods in terms of overall data rate, effective data rate, and number of satisfied users., Comment: 17 pages, 5 figures

Network slicing endows 5G/B5G with differentiated and customized capabilities to cope with the proliferation of diversified services, whereas limited physical network resources may not be able to support all service requests. Slice admission control is regarded as an essential means to ensure service quality and service isolation when the network is under burden. Herein, the scenario where rational tenants coexist with partially competitive network slice providers is adopted. We aim to maximize the long-term average revenue of the network operators through slice admission control, with the feasibility of multidimensional resource requirements, the priority differences among heterogeneous slices, and the admission fairness within each slice taken into account concurrently. We prove the intractability of our problem by a reduction from the Multidimensional Knapsack Problem (MKP), and propose a two-stage algorithm called MPSAC to make a sub-optimal solution efficiently. The principle of MPSAC is to split the original problem into two sub-problems; inter-slice decision-making and intra-slice quota allocation, which are solved using a heuristic method and a tailored auction mechanism respectively. Extensive simulations are carried out to demonstrate the efficacy of our algorithm, the results show that the long-term average revenue of ours is at least 9.6% higher than comparisons while maintaining better priority relations and achieving improved fairness performance., Comment: 16 pages, 6 figures

5G/B5G is envisioned to support various services with the assistance of network slices, each slice instance asks for adequate resources to provide the pre-negotiated service quality to its subscribers. Slice Admission Control (SAC) algorithm is a necessity for Slice Providers (SPs) to guarantee the QoS and QoE of each admitted request with limited resources. In that circumstance, the priority concern of services and the fairness of resource allocation arise as meaningful topics for researchers. The former originates from the innate characteristics of various services supported by 5G networks, and the latter matters because slices are instantiated on shared physical equipment. However, the two issues are mainly investigated separately in the literature or do not receive sufficient research simultaneously. In this work, we study the SAC problem in 5G/B5G networks, aiming at enhancing the fairness degree on the premise of satisfying the necessary priority requirements. We first reinterpret priority as a higher cumulative service acceptance ratio (CSAR), and adopt the uniformity of adjacent CSAR gaps to reflect the fairness. Based on these adjustments, the SAC problem is formulated as a non-linear and non-convex multi-objective optimization. Thus, we propose a heuristic algorithm called Prioritized Slice Admission Control Considering Fairness (PSACCF) to solve it. It introduces the resource efficiency of services to amend priority violations, then promotes fairness by setting the target CSARs for each service type and pushing their actual CSARs toward. Numerous simulations are carried out to compare the performance of PSACCF with two existing algorithms, termed MHPF and AHPF. Results show that our algorithm can achieve a nearly identical priority indicator to the comparisons, as well as at least a 33.6% improvement in fairness degree and a higher minimum average resource utilization.