Antenna allocation and pricing in virtualized massive MIMO networks via Stackelberg game

We study a resource allocation problem for the uplink of a virtualized massive multiple-input multiple-output (MIMO) system, where the antennas at the base station are priced and virtualized among the service providers (SPs). The mobile network operator (MNO) who owns the infrastructure decides the price per antenna, and a Stackelberg game is formulated for the net profit maximization of the MNO, while minimum rate requirements of SPs are satisfied. To solve the bi-level optimization problem of the MNO, we first derive the closed-form best responses of the SPs with respect to the pricing strategies of the MNO, such that the problem of the MNO can be reduced to a single-level optimization. Then, via transformations and approximations, we cast the MNO’s problem with integer constraints into a signomial geometric program (SGP), and we propose an iterative algorithm based on the successive convex approximation (SCA) to solve the SGP. Simulation results show that the proposed algorithm has performance close to the global optimum. Moreover, the interactions between the MNO and SPs in different scenarios are explored via simulations

5G Cellular: Key Enabling Technologies and Research Challenges

The evolving fifth generation (5G) cellular wireless networks are envisioned to provide higher data rates, enhanced end-user quality-of-experience (QoE), reduced end-to-end latency, and lower energy consumption. This article presents several emerging technologies, which will enable and define the 5G mobile communications standards. The major research problems, which these new technologies breed, as well as the measurement and test challenges for 5G systems are also highlighted.Comment: IEEE Instrumentation and Measurement Magazine, to appear in the June 2015 issue. arXiv admin note: text overlap with arXiv:1406.6470 by other author

Joint User-Association and Resource-Allocation in Virtualized Wireless Networks

In this paper, we consider a down-link transmission of multicell virtualized wireless networks (VWNs) where users of different service providers (slices) within a specific region are served by a set of base stations (BSs) through orthogonal frequency division multiple access (OFDMA). In particular, we develop a joint BS assignment, sub-carrier and power allocation algorithm to maximize the network throughput, while satisfying the minimum required rate of each slice. Under the assumption that each user at each transmission instance can connect to no more than one BS, we introduce the user-association factor (UAF) to represent the joint sub-carrier and BS assignment as the optimization variable vector in the mathematical problem formulation. Sub-carrier reuse is allowed in different cells, but not within one cell. As the proposed optimization problem is inherently non-convex and NP-hard, by applying the successive convex approximation (SCA) and complementary geometric programming (CGP), we develop an efficient two-step iterative approach with low computational complexity to solve the proposed problem. For a given power-allocation, Step 1 derives the optimum userassociation and subsequently, for an obtained user-association, Step 2 find the optimum power-allocation. Simulation results demonstrate that the proposed iterative algorithm outperforms the traditional approach in which each user is assigned to the BS with the largest average value of signal strength, and then, joint sub-carrier and power allocation is obtained for the assigned users of each cell. Especially, for the cell-edge users, simulation results reveal a coverage improvement up to 57% and 71% for uniform and non-uniform users distribution, respectively leading to more reliable transmission and higher spectrum efficiency for VWN

Power-efficient resource allocation in NOMA virtualized wireless networks

In this paper, we address a power-efficient resource allocation problem in virtualized wireless networks (VWNs) using non-orthogonal multiple access (NOMA). In this set-up, the resources of one base station (BS) are shared among different service providers (slices), where the minimum reserved rate is considered for each slice for guaranteeing their isolation. The formulated resource allocation problem aiming to minimize the total transmit power subject to the isolation constraints is non-convex and suffers from high computational complexity. By applying complementary geometric programming (CGP) to convert the non-convex problem into the convex form, we develop an efficient iterative approach with low computational complexity to solve the proposed problem. Illustrative simulation results on the performance evaluation of VWN using OFDMA and NOMA indicate significant performance improvement in the VWN when NOMA is used