A Queue-Aware Discrete Scheduling Simulator for Full-Duplex OFDMA Wireless 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 develop an energy efficient resource allocation scheme for orthogonal frequency division multiple access (OFDMA) networks with in-band full-duplex (IBFD) communication between the base station and user equipments (UEs) considering a realistic self-interference (SI) model. Our primary aim is to maximize the system energy efficiency (EE) through a joint power control and sub-carrier assignment in both the downlink (DL) and uplink (UL), where the quality of service requirements of the UEs in DL and UL are guaranteed. The formulated problem is non-convex due to the non-linear fractional objective function and the non-convex feasible set which is generally intractable. In order to handle this difficulty, we first use fractional programming to transform the fractional objective function to the subtractive form. Then, by employing Dinkelbach method, we propose an iterative algorithm in which an inner problem is solved in each iteration. Applying majorization-minimization approximation, we make the inner problem convex. Also, by introducing a penalty function to handle integer sub-carrier assignment variables, we propose an iterative algorithm for addressing the inner problem. We show that our proposed algorithm converges to the locally optimal solution which is also demonstrated by our simulation results. In addition, simulation results show that by applying the IBFD capability in OFDMA networks with efficient SI cancellation techniques, our proposed resource allocation algorithm attains a 75% increase in the EE as compared to the half-duplex system.

In this paper, the resource allocation policy and algorithm for the uplink Orthogonal Frequency Division Multiple Access (OFDMA) network over the fading channel is studied. With the convex optimization theory, the optimal resource allocation is formulated as a weighted ergodic sum rate maximization problem. The theoretical ergodic capacity region with continuous rate adaption and discrete rate adaption is given subject to per-user power constraint. Simulation results show the ergodic capacity region for two-user uplink OFDMA network.

On distributed power control in full duplex wireless networks

Energy harvesting (EH) structure based on the ambient wireless communication technique, has lastly carried out the development approach to widen the existing time of the wireless networks. The energy collecting composition for the half duplex and full duplex wireless networks is examined. By employing the time switching-based relaying (TSR) networks and the Decode-and-Forward (DF) structure, we imply the approximated section of the operation probability and then estimate the throughput of the half-duplex and full-duplex wireless networks. We can see an essential outcome clearly based on the position of relaying, the achievement rate, the noise at the source and the relay as well as the energy transition component in TSR, effect on their outage possibility and throughput. Ultimately, the performances of the full-duplex (FD) and half-duplex (HD) wireless network architectures is different, the results are collected to demonstrate that, for a normal maximal networks, sometimes, FD one are more optimal than HD model and contrariwise, for instance, when the distance between the relay and the transmitter isn’t great, The outage possibility of the HD model is better than FD one. Or when rises \(\eta \), the HD throughput becomes better etc. With the same method, we also get the results illustrate that DF of two antennas is better than that of one antenna. Consequently, based on the practical condition, we determine what model is better.

We proposed an antenna allocation scheme for a full-duplex communication in IEEE 802.11ac WLAN. In the proposed scheme, an access point (AP) with multiple antennas finds the optimal number of the antennas for transmitting and receiving signals to maximize the sum capacity of the uplink and downlink transmissions. We carry out a simulation and show that the proposed scheme can improve the sum capacity in the full-duplex wireless networks.

A channel-aware and queue-aware (CAQA) scheduling scheme is proposed for the downlink of orthogonal frequency division multiple access (OFDMA) networks. The scheduling scheme cooperates with a rate control policy, which controls arrival rates to the base station queues. The network resource allocation is formulated as a utility maximisation problem, which is decomposed into a CAQA OFDMA scheduling problem and a rate control problem. The authors decompose the scheduling problem into subproblems of rate allocation to subcarriers and propose a joint subcarrier assignment and rate allocation (JSARA) solution for the problem. Simulation is conducted to evaluate the performance of JSARA in terms of throughput, queue length and dropping probability. In addition, JSARA performance gain in allocating users’ arrival rates and achieved aggregate utility, in cooperation with a rate control policy, is investigated.

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.

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, we present a joint game-theoretic approach to perform inter-cell interference coordination in uplink multi-cell orthogonal frequency division multiple access networks. The coordinated user scheduling and power allocation are considered simultaneously. We prove the existence of the joint-strategy Nash equilibrium (NE) in which both the user scheduling and power allocation strategy reach NE. Then, we design a distributed joint-strategy iterative algorithm to perform interference-aware resource allocation where only partial information exchange is involved. Simulation results demonstrate the effectiveness of the proposed algorithm.

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.

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.

Energy efficiency (EE) is one fundamental performance metric for design of orthogonal frequency division multiple access (OFDMA) networks besides spectral efficiency (SE). The conventional resource allocation is to maximize data throughput without consideration of EE. In this paper, we propose a new low-complexity resource allocation algorithm to maximize EE, which first meet the quality-of-services (QoS) demand of every user and then assign the rest of subcarriers with criterion of energy efficiency. We also compare this new algorithm with the near-optimal EE algorithm, maximum-power-decrease-first (MPDF), which is proposed in [9]. The proposed algorithm differs from the MPDF algorithm in terms of the number of waterfilling for subcarrier allocation. The waterfilling operation in our proposed algorithm is not related to the number of users so that it reduces the computational complexity significantly. Finally, the simulation results show that the proposed algorithm approach the EE performance of the MPDF algorithm with lower complexity.