Mathematical Problems in Engineering

Volume 2016 (2016), Article ID 6087856, 7 pages

http://dx.doi.org/10.1155/2016/6087856

## A New Swap-Based Frequency-Domain Packet Scheduling Algorithm in OFDMA System with Data Queue Size Constraints

^{1}School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China^{2}School of Engineering, Qufu Normal University, Rizhao 276826, China

Received 6 January 2016; Revised 11 July 2016; Accepted 11 July 2016

Academic Editor: Ruben Specogna

Copyright © 2016 Lin Shao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### Abstract

This paper aims at the frequency-domain packet scheduling (FDPS) problem in orthogonal frequency division multiple access (OFDMA) system. Under users’ data queue size constraints, a new swap-based FDPS algorithm is proposed to achieve further improvement in system throughput. In this algorithm, the swap of physical resource blocks (PRBs) between different users is introduced to give a comprehensive view of the overall scheduling process. Moreover, the proposed algorithm optimizes the choosing method of swap candidates and always tries to select the user who can maximize the throughput improvement. Simulation results demonstrate that this new algorithm can improve the system throughput significantly as well as reduce the resource waste effectively.

#### 1. Introduction

Due to the explosive growth of users’ demand, 3GPP Long Term Evolution (LTE) has been broadly acknowledged as the most promising standard for next generation cellular systems [1]. In LTE downlink, orthogonal frequency division multiple access (OFDMA) is used as the radio access technology for its robustness to multipath fading and higher spectral efficiency [2, 3]. Multiple access is achieved by assigning different frequency portions of the total bandwidth to individual users in OFDMA [4]. The basic radio resource unit of the system bandwidth is called physical resource block (PRB). Before the assignment of PRBs, the instantaneous channel state information (CSI) needs to be collected from users. Such assignment of PRB based on the quality of channels is called frequency-domain packet scheduling (FDPS).

References [5–8] on FDPS have shown potential gains of system capacity with the assumption of the infinitely backlogged queue model. Reference [9–11] focused on PRB allocation to maximize the system throughput regardless of users’ data queue size (i.e., data prepared to be transmitted per unit time). There are other existing works which had a different optimization objective; however, these works did not consider users’ data queue size as well. For example, in [12–14], PRBs are allocated to achieve proportional fairness (PF) among users using the infinitely backlogged queue model. However, this model is not suitable for every situation. Recent studies [15–17] on traffic measurement have shown that part of users have a small amount of data available for transmission during off-peak hours. In this case, if users’ data queue size is neglected, the channel rate of scheduled users may exceed the amount of data prepared to be transmitted per unit time. It may reduce the system throughput, and PRB resources will not be utilized effectively. So the finite data queue size of users should be taken into account.

More attention has been paid to users’ data queue size constraints in recent works. For example, [18] performed optimal resource assignment by taking into account the channel quality as well as queue backlogs of each user. Reference [19] presented a cross-layer design optimization for subchannel and power allocation in OFDMA system with users’ queue status being considered. Reference [20] proposed a new type of queue-aware channel-adapted scheduling technique which can be integrated into different types of scheduling schemes in the LTE network. Users’ data queue size was discussed in [4] and a swap-based FDPS algorithm was put forward to improve the system throughput. In the algorithm, the isolated resource-assignment strategy was replaced in order to approach the optimal outcome. However, more effective swap candidate selection can achieve higher throughput improvement. In this paper, a new swap-based FDPS algorithm is proposed and the choosing method of swap candidates is optimized. Simulation results demonstrate the superior performance of the proposed algorithm in both improving the system throughput and reducing the resource waste.

The rest of this paper is organized as follows. Swap-based FDPS algorithm in [4] is analyzed in Section 2. Our new swap-based FDPS algorithm is proposed in Section 3. Complexity analysis is in Section 4. Simulation results and discussions are in Section 5 and Section 6 gives the conclusions.

#### 2. Analysis of Swap-Based FDPS Algorithm

Existing PF FDPS algorithm schedules PRBs one by one by using PF algorithm on every PRB in turn. The original PF metric is shown in (1) and for each PRB, the user with the maximum metric value will be selected [4]:where is the supportable instantaneous data rate of user on PRB ( is the PRB index) at time and is the average data rate of user until time .

PF metric (1) does not involve the data queue size, so it is likely to provide more service than users’ demand. In order to overcome this shortcoming, PF metric (1) is modified in [4] as follows:where is the data queue size of user when the scheduling procedure is on PRB . is updated using the following formula:

*Remark 1. *The main progress made by PF metric (2) is the introduction of the data queue size. If a user’s channel rate overtakes (or is equal to) its data queue size, the user’s metric value on every unscheduled PRB will be set to zero. This means that the user will not be given PRBs any longer, which by contrast is inevitable when PF metric (1) is used. Extra PRBs given to the user make no contribution to the system throughput and waste the resource as well; hence, PF metric (2) is one step forward of PF metric (1) in improving the system throughput and reducing the resource waste.

In order to illustrate how much resource has been wasted, a new criterion is introduced as follows:where is the supportable data rate of user when a scheduling process of all PRBs is finished and is the data queue size of user before all PRBs are scheduled. Obviously, shows the useless part of and the more is, the more resource waste an algorithm has produced on user . We can use to illustrate how much resource waste an algorithm has produced on all users. Consider a simple example with two users and two PRBs in Table 1. The scheduling result comparison between PF metric (1) and PF metric (2) is shown in Table 2. Suppose that the assignment of PRB 2 is after the assignment of PRB 1.