Tolga Girici

Proportional fair scheduling algorithm in OFDMA-based wireless systems with QoS constraints

In this work we consider the problem of downlink resource allocation for proportional fairness of long term received rates of data users and quality of service for real time sessions in an OFDMA-based wireless system. The base station allocates available power and subchannels to individual users based on long term average received rates, quality of service (QoS) based rate constraints and channel conditions. We formulate and solve a joint bandwidth and power optimization problem, solving which provides a performance improvement with respect to existing resource allocation algorithms. We propose schemes for flat as well as frequency selective fading cases. Numerical evaluation results show that the proposed method provides better QoS to voice and video sessions while providing more and fair rates to data users in comparison with existing schemes.

Uplink resource allocation algorithms for Single-Carrier FDMA systems

We have focused on SC-FDMA based resource allocation in uplink cellular systems. Subchannel and power allocation constraints specific to SC-FDMA are considered. We considered a binary integer programming-based solution recently proposed for weighted sum rate maximization and extended it to different problems. We considered problems such as rate constraint satisfaction with minimum number subchannels and sum-power minimization subject to rate constraints. Besides stating the binary integer programming formulations for these problems, we propose simpler greedy algorithms for the three problems. Numerical evaluations show that the greedy algorithms perform very close to the optimal solution, with much less computation time.

Joint routing and scheduling metrics for ad hoc wireless networks

We address the problems of routing and scheduling in resource-limited ad hoc wireless networks supporting connectionless traffic. Motivated by the novel challenges and trade-offs introduced by ad hoc wireless networks, we propose link metric-based distributed routing and scheduling algorithms. We consider limited transceiver, energy and unlimited bandwidth conditions and our performance criteria are average consumed energy, delay, network lifetime and communication overhead caused by the scheduling algorithm. We evaluate the performance of the metrics by detailed simulations.

A Pricing Based Algorithm for Cell Switching Off in Green Cellular Networks

In this study, we propose a pricing based algorithm that assigns user terminals (UTs) to base stations (BSs) and optimizes the transmission powers in a way that minimizes the energy expenditure. The algorithm takes into account the fixed energy expenditure that occurs even if a BS does not transmit to any UT, therefore the proposed algorithm switches off the unnecessary BSs in order to minimize the total energy expenditure. We compare this algorithm with two benchmarks. One of them is a simple algorithm that connects each UT to the BS with best channel conditions. Transmission powers are then optimized iteratively. The second benchmark is the optimal solution that is found using a branch and bound technique. The numerical evaluations reveal that the pricing based algorithm performs very close to the optimal.

Optimal radio resource management in multihop relay networks

Multihop relay networks (MR) use relay stations (RS) to extend or enhance the coverage of a base station (BS) in a cellular network. The base station is attached to a wired backhaul. Relay stations use wireless transmission to connect to the base station and to the mobile stations (MS), while direct BS-MS connection is also possible. Low cost relay technologies are recently proposed for OFDM based broadband wireless technologies. Especially for low-cost relay stations that have single radio interface how to share the channels and allocate proper amount of bandwidth/power to the base station (BS), relay stations (RSs) and the mobile stations (MSs) is an important issue. This work develops methods for radio resource management in MR networks supporting heterogeneous traffic. We propose a scheduling method, where the transmission of base station to each relay station and transmissions of each relay station to its respective mobile stations (i.e. composite links) are scheduled in a TDMA fashion and the resource allocation in those microcells are performed in an OFDMA manner. We numerically evaluate the performance of our proposed scheme with respect to a number of parameters.

Practical Resource Allocation Algorithms for QoS in OFDMA-Based Wireless Systems

In this work we propose an efficient resource allocation algorithm for OFDMA based wireless systems supporting heterogeneous traffic. The proposed algorithm provides proportionally fairness to data users and short term rate guarantees to real-time users. Based on the QoS requirements, buffer occupancy and channel conditions, we propose a scheme for rate requirement determination for delay constrained sessions. Then we formulate and solve the proportional fair rate allocation problem subject to those rate requirements and power/bandwidth constraints. Simulations results show that the proposed algorithm provides significant improvement with respect to the benchmark algorithm.

Routing with mutual information accumulation in energy-limited wireless networks

We consider the problem of minimum energy unicast routing in the presence of idealistic rateless codes. The nodes on the path are able to accumulate mutual information from the transmissions of the previous nodes on the path. We first consider the case of nodes with unlimited energy and propose an algorithm that outperforms a method proposed in the recent literature. We then consider the case with limited-energy nodes. We prove by counter examples that some properties that hold in the unlimited energy case, do not hold anymore in the limited energy case. Next we describe a suboptimal algorithm and compare its performance with the optimal solution.

Fairness and QoS-Based Resource Allocation in Multihop Relay Networks

In this paper we study the problem of subframe, subchannel and power allocation in OFDMA-based multihop relay networks. The system consists of a base station (BS), a number of relay stations (RS) and mobile stations (MS). We consider frame by frame scheduling, where the frame is divided into two subframes such as BS-RS and RS-MS subframes. We study two different problems, satisfying link rate requirements with minimum weighted total power and maximizing proportional fairness. For the first problem we find the optimal solution and also propose a less complex subframe and bandwidth allocation scheme with good performance. For the second problem, we propose an algorithm that outperforms an existing scheme with less feedback.

Utility-Based Time and Power Allocation on an Energy Harvesting Downlink: The Optimal Solution

In this paper, we consider the allocation of power level and time slots in a frame to multiple users, on an energy harvesting broadcast system. We focus on the offline problem where the transmitter is aware of the energy arrival statistics of a frame before the frame starts. The goal is to optimize throughput in a proportionally fair way, taking into account the inherent differences of channel quality among users. Analysis of structural characteristics of the problem reveals the biconvex nature of the problem. Due to biconvexity, a Block Coordinate Descent (BCD) based optimization algorithm that converges to one of the multiple optima is proposed. Simulation results show that the resulting allocation achieves a good balance between total throughput and fairness.

Optimal Energy Allocation Policies for a High Altitude Flying Wireless Access Point

Inspired by recent industrial efforts toward high altitude flying wireless access points powered by renewable energy, an online resource allocation problem for a mobile access point (AP) travelling at high altitude is formulated. The AP allocates its resources (available energy) to maximize the total utility (reward) provided to a sequentially observed set of users demanding service. The problem is formulated as a 0/1 dynamic knapsack problem with incremental capacity over a finite time horizon, the solution of which is quite open in the literature. We address the problem through deterministic and stochastic formulations. For the deterministic problem, several online approximations are proposed based on an instantaneous threshold that can adapt to short-time-scale dynamics. For the stochastic model, after showing the optimality of a threshold based solution on a dynamic programming (DP) formulation, an approximate threshold based policy is obtained. The performances of proposed policies are compared with that of the optimal solution obtained through DP.