Interference Hypergraph-Based 3D Matching Resource Allocation Protocol for NOMA-V2X Networks

Vehicle-to-everything (V2X) communications are regarded as the key technology in future vehicular networks due to its ability in improving the traffic efficiency and safety, and reducing congestion. Recently, non-orthogonal multiple access (NOMA), as a promising solution in the fifth generation (5G) mobile communication systems, has drawn much attention because it can significantly improve the network throughput and lower the accessing and transmission latency to meet the requirements of many 5G-enabled applications. Noticing these, in this paper, we propose to introduce NOMA in device-to-device (D2D)-enhanced V2X networks, where D2D-enabled resource sharing based on spatial reuse for different V2X communication groups are permitted through centralized resource management. Such an enhanced NOMA-V2X architecture results in a more complicated and challenging interference scenario. In order to efficiently solve the interference management and resource allocation problem in the NOMA-V2X network, we construct a weighted 3-partite interference hypergraph to model the relationships among different communication groups. Then, based on the constructed hypergraph, we further propose an interference hypergraph-based 3-dimensional matching (IHG-3DM) resource allocation protocol with a greedy 3DM algorithm. Simulation results verify the efficiency of our proposed IHG-3DM resource allocation protocol for NOMA-V2X communications in improving the network throughput.

Vehicular communication network is a core application scenario in the fifth generation (5G) mobile communication system which requires ultra high data rate and ultra low latency. Most recently, non-orthogonal multiple access (NOMA) has been regarded as a promising technique for future 5G systems due to its capability in significantly improving the spectral efficiency and reducing the data transmission latency. In this paper, we propose to introduce NOMA in D2D-enabled V2X networks, where resource sharing based on spatial reuse for different V2X communications are permitted through centralized resource management. Considering the complicated interference scenario caused by NOMA and spatial reuse-based resource sharing in the investigated NOMA-integrated V2X networks, we construct an interference hypergraph to model the interference relationships among different communication groups. In addition, based on the constructed hypergraph, we further propose an interference hypergraph-based resource allocation (IHG-RA) scheme with cluster coloring algorithm, which can lead to both effective and efficient QoS-guaranteed resource block (RB) assignment with low computational complexity. Simulation results verify the efficiency of our proposed IHG-RA scheme for NOMA-integrated V2X communications in improving the network sum rate.

Vehicular communication network is a core application scenario in the fifth generation (5G) mobile communication system which requires ultrahigh data rate and ultralow latency. Most recently, nonorthogonal multiple access (NOMA) has been regarded as a promising technique for future 5G systems due to its capability in significantly improving the spectral efficiency and reducing the data transmission latency. In this paper, we propose to introduce NOMA in device-to-device-enhanced vehicle-to-everything (V2X) networks, where resource sharing based on spatial reuse for different V2X communications are permitted through centralized resource management. Considering the complicated interference scenario caused by NOMA and spatial reuse-based resource sharing in the investigated NOMA-integrated V2X (NOMA-V2X) networks, we construct an interference hypergraph (IHG) to model the interference relationships among different communication groups. In addition, based on the constructed IHG, we further propose an IHG-based resource allocation (IHG-RA) scheme with cluster coloring algorithm, which can lead to both effective and efficient resource block assignment with low computational complexity. Simulation results verify the efficiency of our proposed IHG-RA scheme for NOMA-V2X communications in improving the network sum rate.

The rapid evolution of the wireless communication technologies along with the growing number of connected vehicles and the limitation of available radio resources make scheduling tasks very important for the fifth generation (5G) mobile communication system Thus, to handle the challenges of access collisions, the scarcity of spectral efficiency due to the limited bandwidth and massive connectivity, non-orthogonal multiple access (NOMA) schemes have been introduced as a potential solution for 5G wireless networks. Accordingly, this paper presents a new optimal scheduling algorithm for V2X connections called Dynamic Scheduling Algorithm based on NOMA with Priority Assignment for vehicular Networks (DSA-PA-NOMA), which improves performances in terms of Quality of Service (QoS), throughput and bit error rate (BER). The proposed algorithm consider the traffic classification imposed by V2X exigency and aims to maximize the system throughput by taking into account the channel conditions of Vehicular User Equipment (VUE) expressed by the Signal-to-Interference-plus-Noise Ratio (SINR) value. The optimal distribution of the available Resources Blocks (RBs) is based on a dynamic reallocation process depending in the average blocking rate value (ABR) especially for vehicular Safety Traffic (ST).

Recent activity in 4G (fourth generation) mobile communication systems has steeped the race in its implementation at the earliest. 4G wireless being an upcoming standard witnesses burgeoning interest amongst researchers and vendor. It is being designed to allow seamless integration and communication between wireless devices across diverse wireless standards as well as broadband networks wirelessly. Access to different radio technologies is facilitated due to IP-based-4G mobile communication system connecting the user. This paper attempts to make an assessment in development, transition, and roadmap for fourth generation mobile communication system with a perspective of wireless convergence domain and future research issues.

5G has achieved large-scale commercialization across the world and the global 6G research and development is accelerating. To support more new use cases, 6G mobile communication systems should satisfy extreme performance requirements far beyond 5G. The physical layer key technologies are the basis of the evolution of mobile communication systems of each generation, among which three key technologies, i.e., duplex, waveform and multiple access, are the iconic characteristics of mobile communication systems of each generation. In this paper, we systematically review the development history and trend of the three key technologies and define the Non-Orthogonal Physical Layer (NOPHY) concept for 6G, including Non-Orthogonal Duplex (NOD), Non-Orthogonal Multiple Access (NOMA) and Non-Orthogonal Waveform (NOW). Firstly, we analyze the necessity and feasibility of NOPHY from the perspective of capacity gain and implementation complexity. Then we discuss the recent progress of NOD, NOMA and NOW, and highlight several candidate technologies and their potential performance gain. Finally, combined with the new trend of 6G, we put forward a unified physical layer design based on NOPHY that well balances performance against flexibility, and point out the possible direction for the research and development of 6G physical layer key technologies.

This paper investigates various interference canceller structures appropriate for interleave division multiple access (IDMA)-based random access in order to support massive machine-type communications (mMTC) in the fifth generation (5G) mobile communication system. To support massive connectivity in the uplink, a grant-free and contention-based multiple access scheme is essential to reduce the control signaling overhead and transmission latency. To suppress the packet loss due to collision and to achieve multi-packet reception, non-orthogonal multiple access (NOMA) with interference cancellation at the base station receiver is essential. We use IDMA and compare various interference canceller structures such as the parallel interference canceller (PIC), successive interference canceller (SIC), and their hybrid from the viewpoints of the error rate and decoding delay time. Based on extensive computer simulations, we show that IDMA-based random access is a promising scheme for supporting mMTC and the PIC-SIC hybrid achieves a good tradeoff between the error rate and decoding delay time.

Many application scenarios require indoor positioning in fifth generation (5G) mobile communication systems in recent years. However, non-line of sight and multipath propagation lead to poor accuracy in a traditionally received signal strength-based fingerprints positioning system. In this paper, we propose a positioning method employing multivariable fingerprints (MVF) composed of measurements based on secondary synchronization signals (SSS). In the fingerprint matching, we use MVF to train the convolutional neural network (CNN) location classification model. Moreover, we utilize MVF to train the path-loss model, which indicates the relationship between the distance and the measurement. Then, a hybrid positioning model combining CNN and path-loss model is proposed to optimize the overall positioning accuracy. Experimental results show that all three positioning algorithms based on machine learning with MVF achieve accuracy improvement compared with that of Reference Signal Receiving Power (RSRP)-only fingerprint. CNN achieves best performance among three positioning algorithms in two experimental environments. The average positioning error of hybrid positioning model is 1.47 m, which achieves 9.26% accuracy improvement compared with that of CNN alone.

So far, spatial multiplexing techniques in terms of smart antennas or beamforming have been applied independently from time multiplexing schemes or packet scheduling in third generation (3G) mobile communication systems. Time multiplexing schemes or packet scheduling algorithms are used for transmission of delay tolerant data such as E-mail and download services. With the application of beamforming techniques a joint evaluation opportunity arises. This paper introduces a novel approach to jointly evaluate beamforming and scheduling in a two step algorithm. The algorithm is applied to a single site scenario within 3G boundary conditions in order to demonstrate the effects. Joined evaluation shows significant gains over separate evaluation of beamforming and packet scheduling.

Among the key technologies that have been identified as capacity boosters for fifth generation - 5G - mobile networks, are millimeter wave (mmWave) transmissions and non-orthogonal multiple access (NOMA). The large amount of spectrum available at mmWave frequencies combined with a more effective use of available resources, helps improving the overall capacity. NOMA, unlike orthogonal multiple access (OMA) methods, allows sharing the same frequency resources at the same time, by implementing adaptive power allocation. In this paper we present a performance analysis of NOMA in mmWave cells, using OMA as a benchmark. The results show that up to 70% channel capacity gain can be achieved when using NOMA instead of OMA. Most of the NOMA studies to the date focus mainly on the capacity gain; therefore we also present an analysis of the required signal-to-interference-plus-noise ratio (SINR) in NOMA, needed to achieve a target block error rate (BLER). The results show that an average SINR penalty of 12 dB is present when choosing NOMA over OMA.

In this paper, a bidirectional relaying (BR) non-orthogonal multiple access (NOMA) with simultaneous wireless information and power transfer (SWIPT) termed as BR NOMA-SWIPT is proposed and investigated for the Internet of Things (IoT) relay networks. Here, multiple NOMA users in one group can communicate or exchange information with multiple NOMA users in another group through a common energy harvesting (EH) based relay. The EH based relay exploits the radio frequency (RF) energy supplied by the two NOMA user groups to recharge itself, and then it exchanges the information between them. Specifically, the two groups of NOMA users transmit the information intended for the exchange to the relay node using the uplink NOMA protocol. The relay node first harvests the RF energy through the signals of the two group of NOMA users, and then it carries out the exchange of information between two NOMA user groups by using the downlink NOMA protocol. To the best of our knowledge, there is no existing study or research on BR NOMA with SWIPT. Therefore, in this paper, we examine in detail, the performance of BR NOMA-SWIPT enabled IoT relay networks. Specifically, we study a popular EH time switching (TS) relaying architecture with BR and NOMA. We also study the effect of both perfect successive interference cancellation (pSIC) and imperfect SIC (ipSIC) on the proposed BR NOMA-SWIPT system. Analytical expressions for the outage probability and ergodic capacity are mathematically derived. The analytical results of our proposed system model are validated by the simulation results, and representative performance comparisons are presented thoroughly, which not only provides practical insights into the effect of different system parameters on the overall network performance, but it also demonstrates that our proposed BR NOMA-SWIPT can attain significant throughput and capacity gains as compared to conventional BR multiple access schemes.

Vehicular networking belongs to one of the most attractive techniques under the context of 5th Generation (5G) and Beyond 5G (B5G) wireless communication system. It opens diverse new concepts and applications, e.g. Vehicular-to-Vehicular (V2V), Vehicular-to-Infrastructure (V2I). One of the key components to support autonomous driving is to allow vehicles to share information about their awareness of the environment, i.e. perception layer of neighbor vehicles. In this paper, we focus on low overhead, low latency MAC layer design, enabling perception layer sharing in V2V environment, and PHY layer design, enabling Multi-User Detection (MUD) with V2V environment by means of Non-Orthogonal Multiple Access (NOMA), which is one of the key physical layer technologies of 5G New Radio (NR). Numerical results of link level simulation exhibit that our solution generates and exchanges the NOMA user signature flexibly, i.e. supports both synchronous and asynchronous traffic with low bit error rate. Furthermore, it enables small packet communication with low computational complexity, thus low latency.

Mobile traffic, which has increased significantly with the emergence of Fourth generation longterm evolution (4G-LTE) communications and advances in video streaming services, is still currently increasing at an incredible pace. Fifth-generation (5G) mobile communication systems, which were developed to deal with such a drastic increase in mobile traffic, aim to achieve ultra-high-speed data transmission, low latency, and the accommodation of many more connected devices compared to 4G-LTE systems. 5G communication uses high-frequency bandwidth to implement these features, which leads to an inevitable drawback of a high path loss. In order to overcome this disadvantage, small cell technology was developed, and is defined as small, low-power base stations that can extend the network coverage and solve the shadow area problem. Although small cell technology has these advantages, different problems, such as the effects of interference due to the deployment of a large number of small cells and the differences in devices accessing the network, need to be solved. To do so, it is necessary to develop an algorithm for a service method. However, general algorithms have difficulties in responding to the diverse environment of mobile communication systems, such as sudden increase in traffic in certain areas or sudden changes in the mobile population, and machine learning technology has been applied to solve this problem. This study employs a machine learning algorithm to determine small cell connections. In addition, a 5G macro system, the application of small cells, and the application of machine learning algorithms are compared to determine the performance improvement in the machine learning algorithm. Moreover, Support Vector Machine (SVM), Logistic Regression and Decision Tree algorithm are employed to show a training method that uses basic training data and a small cell on-off method, and the performance enhancement is verified based on this method.

In downlink Internet of things (IoT) applications, certain nodes can be given a higher transmission priority than others, and hence might be allocated more transmission resources. Consequently, some nodes may face a resource-starvation problem. To overcome such a predicament, this article proposes an opportunistic non-orthogonal multiple access (NOMA) scheme to enable low priority (LP) nodes (LPNs) to share the transmission resources of high priority (HP) nodes (HPNs) while prioritizing the quality of service (QoS) requirements of the HPNs. In the proposed scheme, the control center (CC) may decide to multiplex the data of one or more LPNs with the HPN data using NOMA, which can improve the network throughput substantially. Such a decision is based on the channel conditions and QoS requirements for the HPNs and LPNs. Hence, the proposed system may operate in one of the following four modes, HPN orthogonal multiple access (OMA), LPN-OMA, (HPN, LPN)-NOMA, and the OFF mode where all nodes are muted. To improve the network efficiency and reduce overhead, the network is considered uncoordinated where the receiving nodes do not receive side information about the selected transmission-mode by the CC, leaving it to the receiving nodes to blindly recognize the transmission-mode. The network complexity and throughput trade-off is considered for fixed and adaptive power assignments. The results show that the proposed system can provide substantial throughput improvement over conventional NOMA transmission. For the example of a pair of HPN and LPN, the maximum throughput gain with opti-mal power allocation is about 0.85 bits/symbol, which implies that the throughput relative improvement is about 9 folds. The article also discuss the challenges and potential solutions of the proposed framework.

Non-orthogonal multiple access (NOMA) is a promising radio access technique for further cellular enhancements toward 5G. Single-user multiple-input multiple-output (SU-MIMO) is one of the key technologies in LTE /LTE-Advanced systems. Thus, it is of great interest to study how to efficiently and effectively combine NOMA and SU-MIMO techniques together for further system performance improvement. This paper investigates the combination of NOMA with open-loop and closed-loop SU-MIMO. The key issues involved in the combination are presented and discussed, including scheduling algorithm, successive interference canceller (SIC) order determination, transmission power assignment and feedback design. The performances of NOMA with SU-MIMO are investigated by system-level simulations with very practical assumptions. Simulation results show that compared to orthogonal multiple access system, NOMA can achieve large performance gains both open-loop and closed-loop SU-MIMO, which are about 23% for cell average throughput and 33% for cell-edge user throughput.