A Joint Game-Theoretic Interference Coordination Approach in Uplink Multi-Cell OFDMA Networks

While helping better utilize the system's resources, full-duplex technologies have the ability to double the efficiency of wireless networks. However, these networks would suffer from added types of interferences, namely self-interference and intra-cell co-channel interference. As such, efficiently addressing scheduling and power allocation in full-duplex networks is vital. In this article, we formulate a queue-aware, fair scheduling and power allocation problem for full duplex orthogonal frequency division multiple access networks. Due to its intractability, we decompose this problem into two: a scheduling problem and a power allocation problem. We compare our proposal to the state-of-the-art, and show that it improves fairness among the user equipment at no cost in the system's performance. Simulation results show a significant increase in throughput values for full-duplex users in comparison with their half-duplex counterparts, and that power allocation saves on expenditure while improving user performance.

In this paper, we investigate the user scheduling and power allocation scheme for a millimeter wave non-orthogonal multiple access system. To reduce the feedback overhead, random beamforming is adopted at a base station. The optimization problem is formulated to maximize the energy efficiency. To solve this problem, we first address the user scheduling and power allocation problem separately, then an iterative algorithm is proposed to jointly optimize the user scheduling and power allocation. Simulation results show that the proposed scheme achieves higher energy efficiency than the conventional scheme.

International audience

Small cell, mmWave, and massive Multi-Input Multi-Output (MIMO) technologies in 5G cellular networks becomes inevitable trend caused by killer applications such as holographic video which is traffic-intensive. In this paper, we study a sequential activation beam selection, user scheduling, and power allocation problem in a mmWave network with massive MIMO utilizing a physical layer preceding technique. We aim to maximize the time-averaged utility of users with a time-averaged transmit power constraint on top of the EdgeSON architecture, which takes advantage of both centralized and distributed characteristics. We decompose the original long-term problem into two-time scales in which solving the problem of choosing beam pattern is run at a slower time scale than solving user scheduling and power allocation. Then, to solve user scheduling and power allocation, we leverage the Lyapunov drift-plus-penalty framework which transforms an original long-term average problem into per-slot modified sub-problems. Since provided per-slot problem to find a set of user scheduling and power allocation is known as NP-hard, we propose a low-complex and practical interference management algorithm, namely CRIM, by introducing two critical users with the highest interference channel gain in intra-BS and inter-BS respectively. Finally, via extensive simulations, we verify and compare the performance of the proposed algorithm and comparing algorithms in a real mmWave network environment.

With the promise of doubling a wireless net-work's capacity, researchers on full-duplex wireless networks need to address multiple issues such as user equipment pairing, power control, and the availability of channel state information. In this paper, we propose a discrete simulator for scheduling and power allocation proposals in full-duplex orthogonal frequency division multiple access networks. Our simulator is queue-aware and adaptable to different scheduling objectives. It enables varying the path-loss model, user distribution, noise conditions, and throughput demands. Additionally, it permits the calculation of packet level performance metrics such as the waiting delay.

In orthogonal frequency division multiple access networks buffer aided non-transparent in-band half duplex decode and forward relay nodes aim to improve coverage and capacity under fairness considerations. Existing centralized radio resource management and inter cell interference coordination schemes achieve these goals at the cost of heavy signalling overhead. Especially for frequency division duplex downlink transmission this is an critical issue. Fully decentralized schemes often focus on different types of frequency reuse schemes with less amount of necessary feedback. Here, it is often overseen that in a practical deployment, the backhaul link quality is the bottleneck of the two hop transmission and needs to be taken into account. Moreover, it is often modelled way too optimistic and necessary co-scheduling with single hop UE further limits the possible data rate. In order to minimize the required overhead this work proposes a hybrid radio resource management (RRM) scheme. The RRM includes synchronous adapted two-hop proportional frequency selective resource scheduling as the decentralized part. Asynchronous subband power allocation scheme with very limited feedback is proposed to maximize the wireless backhaul link quality with no loss for single hop UE. Comprehensive system level simulation results show stable fairness and throughput when minimizing the required feedback and improvements for the backhaul links based on the centralized adapted power allocation including no losses in the overall system. In addition possible energy savings for the shared channel are presented when applying the proposed scheme.

The joint assignment of subcarriers and limited transmission power is addressed as a combinatorial optimization problem in orthogonal frequency division multiple access networks. To ensure fairness among users while jointly minimizing the total transmit power, the minimization of the number of outage subcarriers is considered as the objective function. The proposed scheme enables distinct rate requirement for each user. Optimal and reduced complexity algorithms, based on the application of Hungarian method to randomly weighted complete bipartite graphs, that reduce the outage probability according to the benchmark works while providing considerable power savings are proposed.

SummaryIn this paper, we present a QoS‐driven energy efficient power and subcarrier allocation in green orthogonal frequency division multiple access networks. Our proposed scheme aims at maximizing the effective energy efficiency (EEE), defined as overall effective capacity per total power consumption, subject to given user delay‐QoS requirements and an average sum transmit power constraints. We analytically obtain the uniquely global optimal power and subcarrier using fractional programming, which transforms the fractional program into an equivalent parametric convex program that has a tractable solution. Analytical results show that the optimal solution has the same structure as effective capacity maximization and overall power minimization solutions. Simulation results show that there exists a trade‐off between EEE and delay. When the delay is more stringent, the EEE decreases. Moreover, when the number of subcarriers increase, EEE increases, where a fixed optimal EEE can be achieved regardless of stringency of delay‐QoS requirements. Furthermore, our proposed resource allocation provides significant EEE gains over both the independent resource allocation and overall power minimization schemes. Copyright © 2015 John Wiley & Sons, Ltd.

In this paper, a joint subcarrier and power allocation algorithm is proposed to improve the physical layer security in cooperative orthogonal frequency division multiple access (OFDMA) networks, where several source-destination pairs and one untrusted relay are involved. The relay is friendly and intends to help these pairs to enhance their communications. However, it may be overheard by a malicious eavesdropper at the same time. To optimize the joint subcarrier and power allocation with low complexity, we divide the optimization problem into two simpler subproblems. Firstly, the subcarriers are assigned to the source-destination pairs by employing the dual approach under the assumption that the relay power is equally allocated to all the subcarriers. Then, the relay power is allocated to the subcarriers based on the alternative ascending clock auction mechanism. In addition, we prove that the two subproblems can converge after a finite number of iterations. We also find that the proposed auction is cheat-proof and, thus, can avoid the cheating behaviors in the auction process. Numerical results demonstrate that our proposed algorithm can effectively improve the system sum secrecy rate, and the convergence performance is also desirable.

User scheduling and power allocation for downlink multi-cell multi-carrier NOMA systems

This paper presents efficient interference-mitigation techniques, such as fractional frequency reuse (FFR) and soft frequency reuse (SFR) schemes, in multicell orthogonal frequency division multiple access networks under the composite multipath fading environment, where Rayleigh fading is superimposed over log-normal shadowing. We begin by outlining the obtained explicit expressions of area spectral efficiency in down-link transmission for both FFR and SFR schemes. The theoretical result are shown to be very accurate with their simulated counterparts using Monte Carlo simulations.

Renewable energy (RE) is a promising solution to reduce grid energy consumption and carbon dioxide emissions of cellular networks. However, the benefit of utilizing RE is limited by its highly intermittent and unreliable nature, resulting in low savings in grid energy. To minimize the grid energy cost, we propose to utilize data buffer of user equipments as well as energy storage at the base station (BS) to better adapt the BS resource allocation and hence its energy consumption to the dynamic nature of RE. We consider the scenario of downlink orthogonal frequency division multiple access networks with non-ideal hybrid energy supply. To jointly optimize the energy consumption and the quality of service (QoS) of users, we adopt the weighted sum of users’ utility of data rates and grid energy consumption as our performance metric. We propose a low-complexity online control scheme based on Lyapunov optimization framework. The proposed technique can provide asymptotically optimal performance bound without requiring the stochastic distribution information of RE arrival and channel state condition. The experimental results demonstrate the ability of the proposed approach to significantly improve the performance in terms of grid power consumption and user QoS compared with the existing schemes.

Large-scale multiple-input multiple-output (MIMO) system with tens to hundreds of antennas is getting increasing attention for its very high spectral efficiency and energy efficiency. However, for frequency division duplexing (FDD) system, the cost of CSIT feedback becomes a bottleneck with the BS antennas increasing. To reduce the cost of the downlink training and the CSIT uplink feedback, joint spatial division and multiplexing (JSDM) scheme is proposed by Ansuman Adhikary, et al., which divides users into different groups according to their channel covariance eigenvectors and adopts the two-stage precoding. This paper proposes a joint user selection and power allocation (JUSPA) algorithm for JSDM scheme in massive MIMO downlink systems, which schedules users and allocates power iteratively with the MAX user scheduling and the Lagrange power optimization method. For user scheduling, it is noticed that the intra-group interference is so large that would disturb the user selection. Then the signal-to-interference noise ratio (SINR) of each beam is computed, neglecting the intra-group interference. The simulation results show that the proposed JUSPA algorithm performs better than the average power allocation method in the original JSDM scheme.

Multiuser Orthogonal Frequency Division Multiple Access (OFDMA) networks, such as Long Term Evolution networks, use the frequency reuse-1 model to face the tremendous increase of mobile traffic demands, and to increase network capacity. However, inter-cell interference problems are generated, and they have a negative impact on cell-edge users performance. Resource and power allocation should be managed in a manner that alleviates the negative impact of inter-cell interference on system performance. In this paper, we formulate a novel centralized multi-cell resource and power allocation problem for multiuser OFDMA networks. The objective is to maximize system throughput while guaranteeing a proportional fair rate for all the users. We decompose the joint problem into two independent problems: a resource allocation problem and a power allocation problem. We prove that each of these problems is a convex optimization problem, and that their optimal solution is also an optimal solution to the original joint problem. Lagrange duality theory and subgradient projection method are used to solve the centralized power allocation problem. We study the convergence of our centralized approach, and we find out that it reduces inter-cell interference, and increases system throughput and spectral efficiency in comparison with the frequency reuse-1 model, reuse-3 model, fractional frequency reuse, and soft frequency reuse techniques.

Heterogeneous network is a novel network architecture proposed in Long-Term-Evolution~(LTE), which highly increases the capacity and coverage compared with the conventional networks. However, in order to provide the best services, appropriate resource management must be applied. In this paper, we consider the joint optimization problem of user association, subchannel allocation, and power allocation for downlink transmission in Multi-cell Multi-association Orthogonal Frequency Division Multiple Access (OFDMA) heterogeneous networks. To solve the optimization problem, we first divide it into two subproblems: 1) user association and subchannel allocation for fixed power allocation; 2) power allocation for fixed user association and subchannel allocation. Subsequently, we obtain a locally optimal solution for the joint optimization problem by solving these two subproblems alternately. For the first subproblem, we derive the globally optimal solution based on graph theory. For the second subproblem, we obtain a Karush-Kuhn-Tucker (KKT) optimal solution by a low complexity algorithm based on the difference of two convex functions approximation (DCA) method. In addition, the multi-antenna receiver case and the proportional fairness case are also discussed. Simulation results demonstrate that the proposed algorithms can significantly enhance the overall network throughput.