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

Completion-Time-Driven Scheduling for Uplink NOMA-Enabled Wireless Networks

Efficient scheduling policy is crucial in wireless networks due to delay-sensitivity of many emerging applications. In this work, we consider a joint user pairing and scheduling (UPaS) scheme for multi-carrier non-orthogonal multiple access (MC-NOMA)-enabled wireless networks to reduce the maximum completion time of serving uplink users. The NOMA scheduling problem is shown to be NP-hard and a shortest processing time (SPT)-based strategy to solve the same problem within affordable time and complexity is introduced. The simulation results confirm the efficacy of the proposed scheduling scheme in terms of the maximum completion time in comparison with orthogonal multiple access (OMA) and random NOMA pairing

Distributed learning-based spectrum allocation with noisy observations in cognitive radio networks

This paper studies the medium access design for secondary users (SUs) from a game-theoretic learning perspective. In consideration of the random return of primary users (PUs), a distributed SU access approach is presented based on an adaptive carrier sense multiple access (CSMA) scheme, in which each SU accesses multiple idle frequency slots of a licensed frequency band with adaptive activity factors. The problem of finding optimal activity factors of SUs is formulated as a potential game, and the existence, feasibility, and optimality of Nash equilibrium (NE) are analyzed. Furthermore, to achieve NEs of the formulated game, learning-based algorithms are developed in which each SU independently adjusts its activity factors. Convergence properties of best-response dynamics and log-linear dynamics are studied. Subsequently, by learning other SUs' behavior from locally available information, the convergence with probability of one to an arbitrarily small neighborhood of the globally optimal solution is investigated by both analysis and simulation

Dynamic Non-Orthogonal Multiple Access (NOMA) and Orthogonal Multiple Access (OMA) in 5G Wireless Networks

In this paper, facilitated via the flexible software defined structure of the radio access units in 5G, we propose a novel dynamic multiple access technology selection among orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) techniques for each subcarrier. For this setup, we formulate a joint resource allocation problem where a new set of access technology selection parameters along with power and subcarrier are allocated for each user based on each user's channel state information. Here, we define a novel utility function taking into account the rate and costs of access technologies. This cost reflects both the complexity of performing successive interference cancellation and the complexity incurred to guarantee a desired bit error rate. This utility function can inherently demonstrate the trade-off between OMA and NOMA. Due to non-convexity of our proposed resource allocation problem, we resort to successive convex approximation where a two-step iterative algorithm is applied in which a problem of the first step, called access technology selection, is transformed into a linear integer programming problem, and the nonconvex problem of the second step, referred to power allocation problem, is solved via the difference-of-convex-functions (DC) programming. Moreover, the closed-form solution for power allocation in the second step is derived. For diverse network performance criteria such as rate, simulation results show that the proposed new dynamic access technology selection outperforms single-technology OMA or NOMA multiple access solutions.Comment: 28 pages, 6 figure

Joint Transcoding Task Assignment and Association Control for Fog-assisted Crowdsourced Live Streaming

The rapid development of content delivery networks and cloud computing has facilitated crowdsourced live-streaming platforms (CLSP) that enable people to broadcast live videos which can be watched online by a growing number of viewers. However, in order to ensure reliable viewer experience, it is important that the viewers should be provided with multiple standard video versions. To achieve this, we propose a joint fog-assisted transcoding and viewer association technique which can outsource the transcoding load to a fog device pool and determine the fog device with which each viewer will be associated, to watch desired videos. The resulting non-convex integer programming has been solved using a computationally attractive complementary geometric programming (CGP). The performance of the proposed algorithm closely matches that of the globally optimum solution obtained by an exhaustive search. Furthermore, the trace-driven simulations demonstrate that our proposed algorithm is able to provide adaptive bit rate (ABR) services

Proactive admission control and dynamic resource management in SDN-based virtualized networks

Network virtualization is a promising approach in which common physical resources are shared between service providers. Due to the substrate network limitations such as maximum available memory of each node of the substrate network as well as different service priorities and requirements, resource management in this setup is essential. On the other hand, SDN is bringing a considerable flexibility in resource management by introducing a centralized controller which can monitor all the substrate network states. In this paper, we propose a proactive admission control and dynamic resource management in SDNbased virtualized network in which the number of accepted highpriority virtual network (VN) requests is maximized, subject to both substrate limitations and memory requirement of each VN request. In the proposed formulation, based on the prediction of the substrate network utilization, we reserve resources for upcoming high-priority VN requests. Via simulation, we show that the algorithm can increase the acceptance ratio of the highpriority VN requests up to % 100 where the substrate network is congested, i.e., arrival rates of both high-priority and low-priority VN requests are high

Dual connectivity in backhaul-limited massive-MIMO HetNets: User association and power allocation

With dual connectivity, a mobile user can be served by a macro base station (MBS) and a pico base station (PBS) simultaneously. In this paper, we address the problem of optimizing user-PBS association and power allocation in the uplink such that the network can serve the users’ demand at the minimum cost, where the PBSs are subject to backhaul capacity limitations and minimum rate requirements of users. We show that this non-convex problem can be formulated as a signomial geometric programming (SGP) whose solution can be found by solving a series of geometric programming (GP) problems. Simulation results are provided to demonstrate traffic offloading trend to PBSs for different cost and backhaul capacity settings, confirming the effectiveness of the proposed iterative algorithm. They also show that the output of the proposed algorithm closely matches the global optimal solution with affordable complexity

Outage analysis and power allocation in uplink non-orthogonal multiple access systems

We propose a tractable expression for the outage probability in single-cell uplink non-orthogonal multiple access (NOMA) systems serving an arbitrary number of users. The expression is obtained by approximating the inter-user interference using a shifted-gamma distributed random variable. We then formulate and propose an efficient iterative algorithm for the outage-constrained min-max power allocation problem for the NOMA system. To give a rigorous comparison, we solve the outage-constrained min-max power allocation problem for the orthogonal multiple access (OMA) counterpart where both the user power allocation and the radio resource division pattern are optimized. Simulations confirm the accuracy of the derived outage probability expression for the NOMA system. Also, we demonstrate that fairness among users in terms of transmission power can be achieved by NOMA. Moreover, NOMA can bring significant power savings to the users as compared to OMA

Outage-constrained robust power allocation for downlink MC-NOMA with imperfect SIC

In this paper, we study power allocation for downlink multi-carrier non-orthogonal multiple access (MC-NOMA) systems and examine the effects of residual cancellation errors resulting from imperfect successive interference cancellation (SIC) on the system performance. In the presence of random SIC errors, we study outage probability of minimum reserved rate for individual user and formulate outage-constrained robust optimization to minimize the total transmit power. Since the problem is non-convex due to probabilistic constraints, complementary geometric programming (CGP) and arithmetic geometric mean approximation (AGMA) technique are employed to transform it into a convex form. An efficient iterative algorithm with low computational complexity is developed to solve the optimization problem. Simulation results demonstrate the performance of robust MC-NOMA with imperfect SIC and compare that to non-robust MC-NOMA and orthogonal multiple access (OMA) schemes