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QoE-Aware Power Control and User Grouping in Cognitive Radio OFDM-NOMA Systems
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In this paper, we design and investigate a novel uplink/downlink (UL/DL) non-orthogonal multiple access (NOMA) network using a common relay. Instead of successive interference cancellation (SIC) for UL/DL NOMA systems with fixed decoding order based on the statistical channel state information (CSI), we adopt the dynamic decoding order according to power level of received signals. Specifically, by exploiting the CSI-based dynamic decoding order, better fairness can be achieved and applicable. This decoding scheme is highly suitable for implementing a NOMA system in practice. The closed-form expressions for the users’ outage probabilities are derived, and then an asymptotic analysis is carried out. Insightful discussions with diversity order are provided. Simulations are performed to corroborate the exactness of the theoretical analysis.
Non-orthogonal multiple access (NOMA) has the potential to provide higher throughput than conventional orthogonal multiple access (OMA), which has been considered as a key technology for 5G. NOMA in satellite communication system can provide anytime, anywhere access with improved spectral efficiency and system capacity because of its ubiquitous coverage. However, the characteristics of the satellite channels are different from that of the terrestrial network, i.e., huge time delay and Doppler shift. In this paper, different from the existing works, which mainly focus on the performance of NOMA in static terrestrial base stations and Geostationary orbit (GEO) scenarios, we investigate the performance analysis of downlink NOMA in dynamic low earth orbit (LEO) satellite communication system with Doppler shift considered. We combine NOMA and orthogonal frequency division multiplexing (OFDM) for better spectral efficiency. Our channel model includes both small scale model and large scale model. For simplify, we only consider two users in one spot beam. Besides, we express the performance analysis of downlink NOMA in LEO satellite communication system, like ergodic capacity, outage probability (OP) and mutual information. However, in traditional NOMA scheme, the proceeding error decision of the high power user will cause the deterioration of the subsequent detection performance. Therefore, a symmetrical coding (SC) scheme for different modulation mode is proposed for low power user to get better performance. Finally, simulation results validate the performance of the NOMA scheme is better than that of the OMA scheme. The proposed SC scheme can achieve a prominent increase performance contrasted to the traditional NOMA scheme.
In conventional cognitive radio (CR), the users in secondary network (SN) can only access the idle spectrum when users in primary network (PN) are absent. This novel strategy provides higher spectrum efficiency when detecting the presence of the PN. Hence, spectrum utilization of the traditional scheme can be further improved as exploiting application of non-orthogonal multiple access (NOMA). As combination of CR and NOMA, such CR-NOMA has been proposed to improve spectrum efficiency to adapt to requirements in 5G communications. In this study, the relaying scheme is employed in the SN of the proposed CR-NOMA and the relay is allowed to energy harvesting (EH) from the secondary transmitter to serve signal forwarding to distant secondary users. With this regard, the complex model of EH-assisted CR-NOMA is explored in outage behavior and throughput performance as awareness on imperfect successive interference cancellation (SIC) at the receiver. As most important results, the exact closed-form of the exact outage probability is derived for each NOMA destination by assuming that the channel coefficients among considered links follow Rayleigh distribution. Furthermore, performance gap between two NOMA users can be controlled by various parameters such as transmit power, energy harvesting coefficients and levels of imperfect SIC. Simulation results verify our analytical results.
To cope with rapid growth of video services, we propose a non-orthogonal multiple access (NOMA) based scalable video multicast (NOMA-SVM) framework for mobile networks, by exploiting NOMA's specific potential in scalable video multicast transmission. We consider statistical channels, instead of channels with perfect estimation, in the proposed NOMA-SVM framework in order to capture the realistic channel behaviors. As quality of experience (QoE) is a better metric than throughput for video transmission, QoE-driven power allocation is performed among multiple video layers in the proposed NOMA-SVM framework, in which users can decode video with quality proportional to their channel conditions. Specifically, we formulate the power allocation problem with the goal to maximize the average QoE over all users while guaranteeing the basic services of these users. To solve such a non-convex discrete problem, an optimal algorithm is developed based on the hidden monotonicity of the problem. A suboptimal algorithm is also proposed with much lower complexity in order to meet the practical needs. Simulation results show that the proposed algorithms outperform existing orthogonal multiple access (OMA) and NOMA based algorithms under various multicast scenarios in terms of QoE.
The inevitable next era of smart living requires unprecedented advances in enabling technologies. The building blocks of this era are devices such as sensors, actuators, and Internet of Things (IoT) devices. Machine-Type Communication (MTC), also known as Machine-to-Machine (M2M) communication, constitutes the main enabling technology to support communications among such devices. The massive number of these devices and the immense amount of traffic generated by them require a paramount shift in cellular and non-cellular wireless technologies to achieve the required connectivity. Ultra-Dense Network (UDN) is intuitively one of the most convenient approaches to tackle such requirements of massive connectivity and high throughput found in MTC. In UDNs, small cells are deployed in large densities compared to Human-Type Communication Users (HTCUs) like smartphones and tablets. In a different scope, multiple access techniques also require a paradigm shift to cope with the increasing density of required connections while confined by limited resources. Recently, Non-Orthogonal Multiple Access (NOMA) has received a great attention as an efficacious candidate to enhance the network’s performance compared to traditional Orthogonal Multiple Access (OMA) techniques. For this sake, in this paper, we provide a comprehensive survey and illustrative simulation results on the application of NOMA to support MTC in a UDN environment. First, we give a brief discussion on MTC and its different applications and supporting technologies. Then, we focus our effort on investigating the main challenges facing MTC along with the existing opportunities found in both NOMA and UDN, respectively. Finally, we show via simulations the possible gains of both technologies and conclude by discussing the open problems for future research directions.
Facing the ever-increasing demand for high quality video streaming and the dramatic variations of wireless network environment, adaptive bitrate video streaming (ABS) emerges as a prominent video quality adaptation technique in improving users' quality of experience (QoE). Reinforcement learning (RL)-based ABS and network-assisted ABS can improve users' QoE through resource utilization efficiency enhancement. However, limited network capacity is still the bottleneck of QoE improvement. Considering the potential capacity gain of non-orthogonal multiple access (NOMA), we study network-assisted ABS in NOMA networks. Based on a synchronous video streaming model and the knowledge of channel state information for next segment, a joint optimization problem of resource allocation and bitrate adaptation is formulated to maximize users' QoE and minimize energy consumption. The original problem is NP-hard and intractable due to the interference coordination problem introduced by NOMA and the multi-slot sum rate constraint. We decompose the original problem into the subproblem of joint subchannel assignment and power allocation (JSAPA), and the subproblem of bitrate adaptation (BA) with Lagrange relaxation method. A joint resource allocation and bitrate adaptation (JRABA) algorithm is further proposed to solve the JSAPA and BA subproblems iteratively. Specifically, the JSAPA subproblem is solved by an extended Gale-Shapley matching algorithm and differ of convex (DC) programming method iteratively. For the BA subproblem, appropriate video bitrate is explored with subgradient method. Numerical results validate the effectiveness of the proposed algorithm and reveal that network-assisted ABS in NOMA networks benefits users in achieving higher QoE with less energy consumption, especially when radio resources are insufficient or with large segment size.
The traditional ground industrial internet of things (IIoT) cannot supply wireless interconnections anywhere due to the small-scale communication coverage. In this paper, a multibeam satellite IIoT in Ka-band is proposed to realize wide-area coverage and long-distance transmissions, which uses NOMA for the beam to improve transmission rate. To guarantee QoS for the satellite IIoT, the beam power is optimized to match the theoretical transmission rate with the service rate. The transmission rate for each beam is maximized by optimizing the power allocation proportion of each node subject to the constraints of the total power for the beam and the minimal transmission rate for each node. Satellite-ground integrated IIoT is proposed to use the ground cellular network to supplement the satellite coverage in the blocked areas. The power allocation and network selection for the integrated IIoT are proposed to decrease the transmission cost. Simulation results are provided to validate the superiority of employing NOMA in the satellite IIoT and show lower transmission cost for the integrated IIoT.