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

Reconfigurable and traffic-aware MAC design for virtualized wireless networks via reinforcement learning

In this paper, we present a reconfigurable MAC scheme where the partition between contention-free and contention-based regimes in each frame is adaptive to the network status leveraging reinforcement learning. In particular, to support a virtualized wireless network consisting of multiple slices, each having heterogeneous and unsaturated devices, the proposed scheme aims to configure the partition for maximizing network throughput while maintaining the slice reservations. Applying complementary geometric programming (CGP) and monomial approximations, an iterative algorithm is developed to find the optimal solution. For a large number of devices, a scalable algorithm with lower computational complexity is also proposed. The partitioning algorithm requires the knowledge of the device traffic statistics. In the absence of such knowledge, we develop a learning algorithm employing Thompson sampling to acquire packet arrival probabilities of devices. Furthermore, we model the problem as a thresholding multi-armed bandit (TMAB) and propose a threshold-based reconfigurable MAC algorithm, which is proved to achieve the optimal regret bound

A NOMA-enhanced reconfigurable access scheme with device pairing for M2M networks

This paper aims to address the distinct requirements of machine-to-machine networks, particularly heterogeneity and massive transmissions. To this end, a reconfigurable medium access control (MAC) with the ability to choose a proper access scheme with the optimal configuration for devices based on the network status is proposed. In this scheme, in each frame, a separate time duration is allocated for each of the nonorthogonal multiple access (NOMA)-based, orthogonal multiple access (OMA)-based, and random access-based segments, where the length of each segment can be optimized. To solve this optimization problem, an iterative algorithm consisting of two sub-problems is proposed. The first sub-problem deals with selecting devices for the NOMA/OMA-based transmissions, while the second one optimizes the parameter of the random access scheme. To show the efficacy of the proposed scheme, the results are compared with the reconfigurable scheme which does not support NOMA. The results demonstrate that by using a proper device pairing scheme for the NOMA-based transmissions, the proposed reconfigurable scheme achieves better performance when NOMA is adopted

Efficient LTE/WiFi coexistence in unlicensed spectrum using virtual network entity: Optimization and performance analysis

Long term evolution (LTE) operation in the unlicensed spectrum is a promising solution to address the scarcity of licensed spectrum for cellular networks. Although this approach brings higher capacity for LTE networks, the WiFi performance operating in this band can be significantly degraded. To address this issue, we consider a coordinated structure, in which both networks are controlled by a higher-level network entity. In such a model, LTE users can transmit in the assigned time-slots, while WiFi users can compete with each other by using p-persistent CSMA in their exclusive time-share. In an unsaturated network, at each duty cycle, the TDMA scheduling for LTE users and p values for WiFi users should be efficiently updated by the central controller. The corresponding optimization problem is formulated and an iterative algorithm is developed to find the optimal solution using complementary geometric programming (CGP) and monomial approximations. Aiming to address Quality-ofService (QoS) assurance for LTE users, an upper bound for average delay of these users are obtained. This analysis could be a basis for admission control of LTE users in unlicensed bands. The simulation results reveal the performance gains of the proposed algorithm in preserving the WiFi throughput requirement

Delay-aware and power-efficient resource allocation in virtualized wireless networks

This paper proposes a delay-aware resource provisioning policy for virtualized wireless networks (VWNs) to minimize the total average transmit power while holding the minimum required average rate of each slice and maximum average packet transmission delay for each user. The proposed cross-layer optimization problem is inherently non-convex and has high computational complexity. To develop an efficient solution, we first transform cross-layer dependent constraints into physical layer dependent ones. Afterwards, we apply different convexification techniques based on variable transformations and relaxations, and propose an iterative algorithm to reach the optimal solution. Simulation results illustrate the effects of the required average packet transmission delay and minimum average slice rate on the total transmission power in VWN

Adaptive pilot-duration and resource allocation in virtualized wireless networks with massive MIMO

This paper investigates the resource allocation problem for a virtualized wireless network (VWN) in which each base station (BS) is equipped with a large number of antennas and due to the pilot contamination error, the perfect estimation of channel state information (CSI) is not available. In this case, the duration of pilot sequence transmission plays a critical role on the achieved VWN throughput. Therefore, we consider this parameter as a new optimization variable and propose a novel utility function for the resource allocation problem. The proposed optimization problem is non-convex with high computational complexity. To address this issue, by applying relaxation and variable transformation techniques, we propose a two-step iterative algorithm in which the allocation of power, sub-carrier and number of antennas is first established and then used to optimize the pilot duration. Simulation results reveal that proper pilot duration design improves the VWN performance

Energy-efficient resource allocation in multi-cell virtualized wireless networks

This paper considers the down-link transmission of an OFDMA-based multi-cell virtualized wireless network (VWN) to serve users belonging to ifferent service providers (slices) with the quality-of-service (QoS) requirements in terms of each slice's minimum reserved rate. In order to improve energy efficiency, we formulate a joint base station (BS) assignment, sub-carrier and power allocation problem to minimize the total transmit power of all the BSs subject to the QoS constraints. This problem is inherently a non-convex optimization problem. To tackle its computational complexity, we apply successive convex approximation (SCA) and complementary geometric programming (CGP) to convert the problem into a computationally efficient formulation and propose an iterative algorithm for solving the problem. We introduce a variable called user association factor (UAF) for jointly assigning users to both BSs and sub-carriers. Simulation results illustrate the performance enhancement of the VWN achieved through our formulation for different network scenarios

Energy-efficient robust resource provisioning in virtualized wireless networks

© 2015 IEEE. This paper proposes a robust resource allocation approach in virtualized wireless networks (VWNs) to address the uncertainty in channel state information (CSI) at the base station (BS) due to estimation error and mobility of users. In this set-up, the resources of an OFDMA-based wireless network are shared among different slices where the minimum reserved rate is considered as the quality-of-service (QoS) requirement of each slice. We formulate the robust resource allocation problem against the worst-case CSI uncertainty, aiming to maximize the overall energy efficiency (EE) of VWN in terms of a newly defined slice utility function. Uncertain CSI is modeled as the sum of its true estimated value and an error assumed to be bounded in a specific uncertainty region. The formulated problem suffers from two major issues: computational complexity and energy-efficiency degradation due to the considered error in the maximum extent. To deal with these issues, we consider a specific form of uncertainty region to solve the robust resource allocation problem via an iterative algorithm. The simulation results demonstrate the effectiveness of the proposed algorithms

Joint user-association and resource-allocation in virtualized wireless networks

In this paper, we consider the down-link dynamic resource allocation in multi-cell virtualized wireless networks (VWNs) to support the users of different service providers (slices) within a specific region 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 sum rate, 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 to represent the joint sub-carrier and BS assignment as the optimization variable vector in the 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 problem, Step 1 derives the optimum user-association and subsequently, and for an obtained user-association, Step 2 finds 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. Simulation results reveal a coverage improvement, offered by the proposed approach, of 57% and 71% for uniform and non-uniform users distribution, respectively, leading to higher spectrum efficiency for VWN

Dynamic resource allocation for MC-NOMA VWNs with imperfect SIC

In this work, we investigate the uplink resource allocation problem for virtualized wireless networks (VWNs) supported by multi-carrier non-orthogonal multiple access (MC-NOMA) and present a sensitivity analysis of such a system to imperfect successive interference cancellation (SIC) and various system parameters. The proposed algorithm for power and sub-carrier allocation is derived from the non-convex optimization minimizing power subject to rate and sub-carrier reservations, for which an optimal solution is NP-hard. To develop an efficient solution, we decompose the optimization into separate power and sub-carrier allocation problems and propose an iterative algorithm based on successive convex approximation and complementary geometric programming. Simulation results demonstrate that compared to orthogonal multiple access, for imperfect SIC with residual interference even up to 10%, the proposed algorithm for MC-NOMA can offer significant improvement in spectrum and power efficienc