Utility maximisation in channel-aware and queue-aware orthogonal frequency division multiple access scheduling based on arrival rate control

In this paper, we propose fairness-oriented packet scheduling (PS) schemes with power-efficient control mechanism for future packet radio systems. In general, the radio resource management functionality plays an important role in new OFDMA based networks. The control of the network resource division among the users is performed by packet scheduling functionality based on maximizing cell coverage and capacity satisfying, and certain quality of service requirements. Moreover, multiantenna transmit-receive schemes provide additional flexibility to packet scheduler functionality. In order to mitigate inter-cell and co-channel interference problems in OFDMA cellular networks soft frequency reuse with different power masks patterns is used. Stemming from the earlier enhanced proportional fair scheduler studies for single-input multiple-output (SIMO) and multiple-input multipleoutput (MIMO) systems, we extend the development of efficient packet scheduling algorithms by adding transmit power considerations in the overall priority metrics calculations and scheduling decisions. Furthermore, we evaluate the proposed scheduling schemes by simulating practical orthogonal frequency division multiple access (OFDMA) based packet radio system in terms of throughput, coverage and fairness distribution among users. As a concrete example, under reduced overall transmit power constraint and unequal power distribution for different sub-bands, we demonstrate that by using the proposed power-aware multi-user scheduling schemes, significant coverage and fairness improvements in the order of 70% and 20%, respectively, can be obtained, at the expense of average throughput loss of only 15%.

In this paper, we propose a joint resource allocation, routing, and connection admission control (CAC) scheme for uplink transmission in orthogonal frequency division multiple access (OFDMA) relay networks with cooperative relaying. For cooperative relaying, relay station can relay uplink data from mobile station (MS) to base station with cooperation of the MS using transmit diversity. Transmit diversity can be achieved by virtual MISO via distributed space---time coding. The proposed scheme jointly allocates OFDMA resources and selects path for each user with CAC to maximize the upink throughput of cooperative OFDMA relay networks. The basic OFDMA resource unit is considered as a resource element which is one subcarrier over one OFDMA symbol. An efficient multi-choice multi-dimensional knapsack (MMKP) algorithm is presented for the proposed scheme. The proposed MMKP algorithm provides a unified framework which is applicable to OFDMA networks with and without cooperative relaying. We evaluate the performance of the proposed scheme with and without cooperative relaying in a hilly terrain with heavy tree density by using OPNET-based simulation. We show that the cooperative relaying improve the uplink system throughput compared with non-cooperative relaying, and the proposed scheme outperforms the conventional link quality-based scheme in both cooperative and non-cooperative relay 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.

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.

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 formulate an optimization problem for resource allocation and scheduling in orthogonal frequency division multiple access (OFDMA) networks. Our problem formulation takes into account artificial noise generation to combat a passive multiple antenna eavesdropper and the effects of imperfect channel state information at the transmitter (CSIT) in slow fading. The optimization problem is solved by dual decomposition which results in an iterative resource allocation algorithm with a fast speed of convergence. The packet data rate, secrecy data rate, power, and subcarrier allocation policies are optimized to maximize the average secrecy outage capacity (bit/s/Hz securely and successfully delivered to the users). Simulation results illustrate that our proposed iterative algorithm converges to the optimal solution in a small number of iterations and guarantees a non-zero secrecy data rate for given target secrecy outage and channel outage probability requirements.

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.

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.

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.

In the modern world, a high-speed wireless Internet connection is a necessity rather than a luxury. To improve the efficiency of Wi-Fi networks in dense deployment, a novel amendment to the Wi-Fi standard, namely IEEE 802.11ax introduces Orthogonal frequency-division multiple access (OFDMA). In contrast to legacy Wi-Fi, where performance of a station to a considerable degree depends on rate control, aggregation and other decision-making algorithms implemented at the station, in 11ax networks it is the access point that schedules channel time and specifies transmission parameters for both uplink and downlink. Although OFDMA scheduling in 11ax has much in common with that in cellular networks, e.g. LTE, 11ax has some peculiarities, especially for uplink transmission. Focusing on such peculiarities, in this paper, we investigate the scheduling problem in 11ax, propose a set of schedulers for 11ax, compare their performance and determine the gain achievable by the usage of OFDMA.

In this paper, we mathematically derive a matrix-form solution named resource allocation matrix (RAM) for sub-band allocation in an orthogonal frequency division multiple access (OFDMA) system. The proposed scheme is designed to enhance throughput under a strict user fairness condition such that every user has an equal number of sub-bands per frame. The RAM designates the most preferable sub-band for every user. The proposed scheme is evaluated in terms of throughput and user fairness by comparison with the proportional fairness (PF) scheme and greedy scheme. Numerical results show that the proposed scheme has overwhelming superiority to other schemes in terms of fairness and tight competitive in terms of throughput.

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.

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.

Efficient resource allocation for delay-sensitive traffic, such as telephony and video streaming, in Orthogonal Frequency Division Multiple Access (OFDMA) networks is needed to increase system performance. In our system, users try to achieve a low queuing delay and buffer space usage by competing for transmission over the subchannels. We formulate this problem as a bargaining game and use the Nash Bargaining Solution (NBS) to realize a fair and efficient subchannel allocation for the users. Simulation results show performance improvements, with regard to packet dropping and delay distribution, over other algorithms.

In this study, the physical layer resource allocation in orthogonal frequency‐division multiple access (OFDMA) systems is studied by considering the non‐linear effects of power amplifier (PA). The non‐linearity produces cross‐correlation among the subcarriers and results in deteriorating the OFDMA subcarriers orthogonality. Hence, the signal‐to‐interference ratio (SIR) of the output signal of PA for OFDMA signal with different power scaling factors for subcarriers is derived. Then, the theoretical SIR is verified by simulation result. Next, the optimisation problem is designed to maximise the total achievable downlink rate of all users by assigning subcarriers and power scaling factors. This non‐convex problem is solved by comprehensive learning particle swarm optimisation. The simulation results show that when PA is non‐linear, better total rate is achieved by considering non‐linearity in resource allocation compared with the conventional resource allocation techniques.