0018-9545 (c) 2016 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TVT.2016.2635262, IEEE Transactions on Vehicular Technology IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. XX, NO. YY, MONTH 2016 1 Uplink Scheduling and Power Allocation for M2M Communications in SC-FDMA based LTE-A Networks with QoS Guarantees Fayezeh Ghavimi, Student Member, IEEE, Yu-Wei Lu, and Hsiao-Hwa Chen, Fellow, IEEE Abstract—Providing diverse and strict quality of service (QoS) guarantees is one of the most important requirements in M2M communications, which particularly need for appropriate re- source allocation for a large number of M2M devices. To efficiently allocate resource blocks (RBs) for M2M devices while satisfying QoS requirements, we propose group based M2M com- munications, in which M2M devices are clustered based on their wireless transmission protocols, their QoS characteristics and requirements. To perform joint RB and power allocation in SC- FDMA based LTE-A networks, we formulate a sum-throughput maximization problem, while respecting all the constraints associ- ated with SC-FDMA scheme as well as QoS requirements in M2M devices. The constraints in uplink SC-FDMA air interface in LTE-A networks complicate the resource allocation problem. We solve the resource allocation problem by first transforming it into a binary integer programming (BIP) problem, and then formulate a dual problem using the Lagrange duality theory. Numerical results show that the proposed algorithm outperforms traditional Greedy algorithm in terms of throughput maximization while satisfying QoS requirements, and its performance is close to the optimal design. Index terms—M2M communication; LTE-Advanced; Scheduling; Grouping; Power allocation; SC-FDMA; Resource allocation; QoS. I. INTRODUCTION Recently, wireless communications have been extensively used to exchange data among individuals. In addition to human-to-human (H2H) communications, the introduction of machine-to-machine (M2M) communications in cellular net- works has extended the wireless connectivity to machines. In order to enable machine automation and thus to take full advantages of the opportunities created by a global M2M communications over cellular networks, the 3GPP LTE-A networks offer higher capacity and more flexible radio re- source management (RRM) schemes than the existing packet access data technologies [1]. In LTE-A, various stations can be configured (e.g., evolved universal terrestrial radio access (E-UTRA) NodeBs (eNBs), home eNBs (HeNBs), and relay nodes (RNs)) to provide comprehensive wireless access in both outdoor and indoor environments. Via attaching to those Fayezeh Ghavimi (email: faiezeh.ghavimi@gmail.com), Yu-Wei Lu (email: u.master.o.twn@gmail.com), and Hsiao-Hwa Chen (email: hshwchen@ieee.org) are with the Department of Engineering Science, National Cheng Kung University, 1 Da-Hsueh Road, Tainan City, 70101, Taiwan. This work was supported in part by Taiwan Industrial Technology Research Institute (ITRI) research grant No. M0-10309-6, and Taiwan Ministry of Science and Technology grant No. 104-2221-E-006-081-MY2. The paper was submitted on May 16, and revised on Oct 1. stations, higher-layer connections among all M2M devices can be provided, in which LTE-A was designed basically for wideband applications in order to support multimedia transmissions of a large amount of data with a high throughput. However, there are two important challenges in enabling M2M communications in LTE-A networks as described in the sequel. The first important challenge is that LTE-A networks were designed basically for H2H communications, where the amount of uplink (UL) traffic is normally lower than the downlink (DL) traffic. In contrast, M2M traffic is distinct from the H2H traffic and more traffic data can be generated in UL channels than that over DL channels. Thus, congestion could happen due to concurrent transmit messages from massive M2M devices, which leads to a low successful rate of random access (RA), and thus both M2M devices and UEs suffer con- tinuous collisions in physical random access channel (PRACH) [2]-[3]. In the literature, some approaches have been studied for controlling PRACH overload problem [4]-[11], which will be explained in the next section. Another challenge is due to diverse quality of service (QoS) provision for M2M devices, which plays a critical role in M2M communication networks. Depending on their distinct QoS requirements, different M2M devices are expected to be sensitive to different QoS metrics. For instance, non-real time M2M applications, such as data transmissions, aim to maximize the reliability with a not-so-strict delay constraint. In contrast, for real-time M2M applications, such as video demand, a critical QoS metric is to ensure a stringent delay- bound and rate requirement, rather than to achieve a high spectral efficiency. Furthermore, there also exist some M2M applications falling in between the aforementioned two sit- uations (e.g., paging signals), which are delay-sensitive but do not require so stringent QoS requirements as real time M2M applications. Therefore, different M2M devices impose very much different and sometimes even conflicting QoS constraints, which are the challenges to the designs of efficient radio resource allocation algorithms for M2M communications in LTE-A networks. Current research efforts have been made to consider more sophisticated applications for extracting more realistic and precise information of highly unpredictable channels in the real world, and to deal with them in a responsive manner, where each M2M device performs various tasks ranging from sensing, decision making, and mission executing [1]. Wireless multimedia sensor networking (WMSN), as a powerful and intelligent class of M2M systems, has gained its popularity