Abstract
To alleviate random access congestion and support massive-connections with less energy consumption for machine-type communications (MTC) in the 5G cellular network, we propose an efficient resource allocation for massive MTC (mMTC) with hybrid non-orthogonal multiple access (NOMA)-orthogonal frequency division multiple access (OFDMA). First, a hybrid multiple access scheme, including the NOMA-based congestion-alleviating access scheme (NCAS) and OFDMA-based congestion-alleviating access scheme (OCAS), is proposed, in which the NOMA based devices coexist with OFDMA based ones. Then, aiming at maximizing the system access capacity, a traffic-aware resource blocks (RBs) allocation is investigated to optimize RBs allocation for preamble transmission and data packets transmission, as well as to optimize the RBs allocation between NCAS and OCAS for the RBs usage efficiency improvement. Next, aiming at the problem of high computational complexity and improving energy efficiency in hybrid NOMA-OFDMA based cellular M2M communications, this paper proposes an improved low complexity power allocation algorithm. The feasibility conditions of power allocation solution under the maximum transmit power constraints and quality of service (QoS) requirements of the devices is investigated. The original non-convex optimization problem is solved under the feasibility conditions by two iterative algorithms. Finally, a device clustering scheme is proposed based on the channel gain difference and feasible condition of power allocation solution, by which NOMA based devices and OFDMA based devices can be determined. Simulation results show that compared with non-orthogonal random access and transmission (NORA-DT), the proposed resource allocation scheme for hybrid NOMA-OFDMA systems can efficiently improve the performance of access capacity and energy efficiency.
Highlights
Machine-type communications (MTC), known as machine-to-machine (M2M)communications, is an emerging technology that boosts the development of the Internet of Things (IoT) by providing ubiquitous connectivity and services [1,2]
The first sub-problem is used to optimize resource blocks (RBs) allocation between physical random access channel (PRACH) and physical uplink shared channel (PUSCH) given the sum of RBs allocated to PRACH and PUSCH for NOMA-based congestion-alleviating access scheme (NCAS), while the second one optimizes the RBs allocation between NCAS and OFDMA-based congestion-alleviating access scheme (OCAS)
The first sub-problem is used to optimize RBs allocation between PRACH and PUSCH given the sum of RBs allocated to PRACH and PUSCH for NCAS, while the second one optimizes the RBs allocation between NCAS and OCAS since the MTCDs may not be able to process over the whole available RBs
Summary
Communications, is an emerging technology that boosts the development of the Internet of Things (IoT) by providing ubiquitous connectivity and services [1,2]. We propose a traffic-aware resource allocation scheme for hybrid NOMA-OFDMA based cellular M2M communications. The MTCDs in NCAS and OCAS are allowed to send data with optimal power allocation solution right after preamble transmission without explicitly establishing a connection, which could reduce the scheduling signaling overhead and simplify the access process. To alleviate the RA congestion problem, the number of MTCDs that compete for uplink resources allocated for NCAS and OCAS are restricted by the traffic-aware access barring schemes. If the channel gain differences among devices can satisfy the condition of grouping, these devices are treated as NOMA based MTCDs, which compete for uplink resources allocated for NCAS. We evaluate the energy efficiency and access capacity performance of the resource allocation for the hybrid NOMA-OFDMA based cellular M2M communication systems. X \ x denotes that component x is not included in the set X , and X (m) denotes the m-th element of set X
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
