A Heuristic for Maximising Energy Efficiency in an OFDMA System Subject to QoS Constraints (original) (raw)
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A heuristic for maximising energy efficiency in OFDMA systems with QoS constraints
2018
OFDMA is a popular coding scheme for mobile wireless multichannel multiuser communication systems. In a previous paper, we used mixed-integer nonlinear programming to tackle the problem of maximising energy efficiency, subject to certain quality of service (QoS) constraints. In this paper, we present a heuristic for the same problem. Computational results show that the heuristic is at least two orders of magnitude faster than the exact algorithm, yet yields solutions of comparable quality.
International Journal of Communication Systems, 2015
Energy efficiency (EE) has currently turn into one of the major issues in heterogeneous networks (HetNet) paradigm of today's wireless communication industry. In this paper, we optimize EE for downlink OFDMA system in HetNet, taking into account realistic network power consumption model, that is, considering circuit power. This paper investigates the EE maximization using convex optimization theory where primary optimization criterion is data rate in a downlink multiuser HetNet. Given QoS (data rate) requirement, for maximizing EE, a constrained based optimization problem is devised. Because the optimization problem is non-convex in nature, we reconstruct the optimization problem as a convex one and devise a pragmatically efficient novel resource assignment algorithm for maximizing achievable EE, with quick convergence. The considered optimization problem is transformed into a convex optimization problem by redefining the constraint using cubic inequality, which results in an efficient iterative resource allocation algorithm. In each iteration, the transformed problem is solved by using dual decomposition with a projected gradient method. Analytical insights and numerical results exhibit the potency of the devised scheme for the targeted complex wireless systems.
It is widely recognized that besides the quality of service (QoS), the energy efficiency is also a key parameter in designing and evaluating mobile multimedia communication systems, which has catalyzed great interest in recent literature. In this paper, an energy efficiency model is first proposed for multiple-input multiple-output orthogonal-frequency-divisionmultiplexing (MIMO-OFDM) mobile multimedia communication systems with statistical QoS constraints. Employing the channel matrix singular-value-decomposition (SVD) method, all subchannels are classified by their channel characteristics. Furthermore, the multi-channel joint optimization problem in conventional MIMO-OFDM communication systems is transformed into a multi-target single channel optimization problem by grouping all subchannels. Therefore, a closed-form solution of the energy efficiency optimization is derived for MIMO-OFDM mobile mlutimedia communication systems. As a consequence, an energy-efficiency optimized power allocation (EEOPA) algorithm is proposed to improve the energy efficiency of MIMO-OFDM mobile multimedia communication systems. Simulation comparisons validate that the proposed EEOPA algorithm can guarantee the required QoS with high energy efficiency in MIMO-OFDM mobile multimedia communication systems.
IEEE Access, 2017
Most of the resource allocation literature on the energy-efficient orthogonal frequency division multiple access (OFDMA)-based wireless communication systems assume continuous power allocation/control, while, in practice, the power levels are discrete (such as in 3GPP LTE). This convenient continuous power assumption has mainly been due to either the limitations of the used optimization tools and/or the high computational complexity involved in addressing the more realistic discrete power allocation/control. In this paper, we introduce a new optimization framework to maximize the energy efficiency of the downlink transmission of cellular OFDMA networks subject to power budget and quality-of-service constraints, while considering discrete power and resource blocks (RBs) allocations. The proposed framework consists of two parts: 1) we model the predefined discrete power levels and RBs allocations by a single binary variable and 2) we propose a close-to-optimal semidefinite relaxation algorithm with Gaussian randomization to efficiently solve this non-convex combinatorial optimization problem with polynomial time complexity. We notice that a small number of power levels suffice to approach the energy efficiency performance of the continuous power allocation. Based on this observation, we propose an iterative suboptimal heuristic to further reduce the computational complexity. Simulation results show the effectiveness of the proposed schemes in maximizing the energy efficiency, while considering the practical discrete power levels.
Energy Efficient Resource Allocation in Two-Tier OFDMA Networks with QoS Guarantees
Wireless Networks, 2017
In this paper, we study joint power and subchannel allocation problem for OFDMA based femtocell networks with focus on uplink direction. We minimize the aggregate power of all Femto user equipments and maximize the total system energy efficiency while satisfying the minimum required rate of all users. An interference limit constraint is considered to protect the QoS of macrocells. The original problem is a mixed-integer non-convex optimization problem which is converted to a convex problem using the time-sharing concept. Three algorithms are proposed to provide a scheme to optimize the goal function while meeting the constraints. The complexity order of all algorithms was investigated and was compared to other alternative solutions. The analytic and simulation results have demonstrated that the proposed algorithms could achieve significant power saving and better energy efficiency compared to existing algorithms.
Energy-efficient resource allocation in wireless OFDMA systems
2010
Reducing the consumed energy in wireless communication systems has a direct impact on operational expenditure as well as CO2 emissions. With increasing interest in multimedia applications and high data rate services, environmentally sustainable communications networks must reduce the energy per delivered bit at an equal rate, if not better. This paper addresses downlink energy-efficient transmission in OFDMA systems and maximizes the overall bits transmitted per joule of energy. In addition to the transmit power, circuit power is also accounted for in the energy-efficient design, which is tackled using both standard optimization techniques and a frame work based on time-sharing. Simulation results show similar performances for both cases with the latter having lower complexity and taking less CPU time to run.
IEEE Transactions on Communications, 2015
This paper investigates the joint transmitter and receiver optimization for the energy efficiency (EE) in orthogonal frequency-division multiple-access (OFDMA) systems. We first establish a holistic power dissipation model for OFDMA systems, including the transmission power, signal processing power, and circuit power from both the transmitter and receiver sides, while existing works only consider the one side power consumption and also fail to capture the impact of subcarriers and users on the system EE. The EE maximization problem is formulated as a combinatorial fractional problem that is NP-hard. To make it tractable, we transform the problem of fractional form into a subtractive-form one by using the Dinkelbach transformation and then propose a joint optimization method, which leads to the asymptotically optimal solution. To reduce the computational complexity, we decompose the joint optimization into two consecutive steps, where the key idea lies in exploring the inherent fractional structure of the introduced individual EE and the system EE. In addition, we provide a sufficient condition under which our proposed two-step method is optimal. Numerical results demonstrate the effectiveness of proposed methods, and the effect of imperfect channel state information is also characterized.
Engineering Science and Technology, an International Journal, 2020
In this article, we devise two efficient radio resource allocation algorithms in order to increase fair energy efficiency among users of OFDMA networks. The objective function is considered to be the well-known max-min function in order for allocating radio resources fairly in terms of energy efficiency, by taking the maximum transmit power, minimum rate requirements, and subchannel assignment constraints into account. The resulting problem is a nonconvex mixed-integer nonlinear problem for which two algorithms are proposed. In the first proposed algorithm, by reallocating the transmit power on subchannels, we obtain a suitable subchannel assignment with high fair energy efficiency. In the second proposed algorithm, by applying generalized fractional programming, mathematically modifying the objective function and constraints to a continuous and convex form and employing sequential convex programming, we allocate power and subchannel jointly. The proposed algorithms efficiently utilize radio resources and therefore, yield a far better performance than available solutions.
Energy-Efficient Subcarrier-and-Bit Allocation in Multi-User OFDMA Systems
2012 IEEE 75th Vehicular Technology Conference (VTC Spring), 2012
Energy efficiency is becoming increasingly important for wireless communication systems in order to minimize carbon footprint of wireless networks and to increase the battery life of mobile terminals. The spectral-energy efficiency trade-off is of primary significance to determine how much energy per bit is required in a wireless communication system to achieve a specific spectral efficiency. In this paper, we study energyefficient resource allocation scheme for Orthogonal Frequency-Division Multiple Access (OFDMA) systems with multiple users. The trade-off between spectral and energy efficiencies is analyzed under the constraint of maintaining the fairness among users. We first formulate the energy-efficient optimization problem as an integer fractional programming. We then apply an iterative fractional method to simplify the problem to integer linear programming (ILP) problem. Simulation results demonstrate that the impact of user's quality of service (QoS) is minor on the energy efficiency when a large spectral efficiency is required.
Power/Rate Optimization of OFDMA
Abstract—The demand for mobile broadband access has been on the rise. The growth is not only in the data rate but also in access method, where and when to access the data network are all changing dynamically. The increase in demand requires the network vendors, operators and researchers to increasing look for ways to satisfy and exceed the demand of the consumers, the subscribers or the data users. OFDMA is one of the major breakthroughs of the recent time by network operators, vendors and especially researchers to satisfy this interest with the next generation Networks that will guarantee that this demand is met and suppassed. Wireless broadband access system adopts OFDM and OFDMA formats for the multi-carrier signals to meet and exceed the current increase in demand for data applications in a wireless environment. The requirement of (ITU-R/IMT) International Telecommunication Union-Radio communication Sector/International Mobile Telecommunications-Advanced group specified that the cell spectral efficiency which is the ratio of aggregate throughput of all users to the product of the bandwidth and the number of cells is the most important of all the specification [8]. In this report I reviewed 5 Algorithms used in Power/Rate optimization of the OFDMA system in mobile communication environment. My study shows that the Power/rate optimization is a complex problem but can be approached by using known parameters to estimate unknown variables while making sure that all the constraints are considered.