In this paper, we investigate the performance of the non-orthogonal multiple access (NOMA) system with incremental relaying, where the relay is employed with amplify-and-forward (AF) or decode-and-forward (DF) protocols. To characterize the outage behaviors of the incremental cooperative NOMA (ICN) system, new closed-form expressions of both exact and asymptotic outage probability for two users are derived. In addition, the performance of the conventional cooperative NOMA (CCN) system is analyzed as a benchmark for the the purpose of comparison. We confirm that the outage performance of the distant user is enhanced when ICN system is employed. Numerical results are presented to demonstrate that (1) the near user of the ICN system achieves better outage behavior than that of the CCN system in the low signal-to-noise ratio (SNR) region; (2) the outage performance of distant user for the DF-based ICN system is superior to that of the AF-based ICN system when the system works in cooperative NOMA transmission mode; and (3) in the low SNR, the throughput of the ICN system is higher than that of the CCN system. authors of [9] have researched the performance of a downlink single-cell NOMA network when assuming imperfect channel state information (CSI) and second-order statistics. Furthermore, the authors in [10] consider the scenario that each user only feedback one bit of its CSI to a base station (BS) and analyzed the outage performance. Apart from these researches, there are a lot of studies on improving the secrecy performance of multiple users [11,12], where the external and internal eavesdropping scenarios have been considered. Up to now, NOMA has been extended to cooperative communication systems [13, 14], as the higher diversity and extended coverage can be obtained in wireless networks. The authors have analyzed the outage performance of NOMA system with decode and forward (DF) relay employing full-duplex (FD) and half-duplex (HD) mode, where the near user was selected as a relay to deliver information and improve transmission reliability of distance users [15]. Inspired by this, simultaneous wireless information and
Mobile edge computing (MEC) is a promising technique to meet the demands of computing-intensive and delay-sensitive applications by providing computation and storage capabilities in close proximity to mobile users. In this paper, we study energy-efficient resource allocation (EERA) schemes for hierarchical MEC architecture in heterogeneous networks. In this architecture, both small base station (SBS) and macro base station (MBS) are equipped with MEC servers and help smart mobile devices (SMDs) to perform tasks. Each task can be partitioned into three parts. The SMD, SBS, and MBS each perform a part of the task and form a three-tier computing structure. Based on this computing structure, an optimization problem is formulated to minimize the energy consumption of all SMDs subject to the latency constraints, where radio and computation resources are considered jointly. Then, an EERA mechanism based on the variable substitution technique is designed to calculate the optimal workload distribution, edge computation capability allocation, and SMDs’ transmit power. Finally, numerical simulation results demonstrate the energy efficiency improvement of the proposed EERA mechanism over the baseline schemes.
Mobile edge computing (MEC) is a promising paradigm for providing computing and storage capabilities in close proximity to mobile devices. To solve the scenario in which massive mobile devices have tasks to be processed at the same time, this paper proposes an assisted mechanism for the MEC system. When the primary MEC server is unable to meet the delay requirements of the mobile devices within its coverage area, a portion of the tasks can be offloaded to secondary MEC servers to obtain extra resources for processing. This MEC framework effectively reduces the computing and communication burden of the primary MEC server and improves the resource utilization of the secondary MEC servers. To maximize the system offloading utility in terms of latency, we formulated an optimization problem that jointly optimizes the task assignment, computing resource allocation and offloading decision of all mobile devices. Since the formulated problem is a mixed integer nonlinear problem, we use the decomposition method to convert the optimization problem into several subproblems. In addition, a heuristic algorithm based on the priorities of mobile devices and the MEC servers is proposed to obtain the suboptimal device offloading strategy. The numerical results show that the assisted mechanism can effectively reduce system latency and improve system reliability. In addition, the performance of our proposed algorithm is close to the optimal solution. INDEX TERMS Assisted mechanism, computation offloading scheme, mobile edge computing, resource allocation.
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