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 providing efficient and reliable massive connections, improving traffic efficiency and safety, and supporting in-vehicle entertainment and working. 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 quality-of-service (QoS) requirements of many 5G-enabled applications. Noticing these, in this paper, we consider a device-to-device (D2D)-enhanced V2X network, in which NOMA is introduced to increase the capacity. In our studied NOMA-V2X system, except for the NOMA-based intra-group resource reuse, the D2D-enabled resource sharing based on spatial reuse among all the V2X communication groups is also permitted through centralized resource management, leading to a significantly improved network performance but a more complicated and challenging interference scenario. In order to efficiently manage the interference and allocate the resource in the NOMA-V2X network, we create a weighted 3-partite interference hypergraph (IHG) to imitate the complex interference environment in our studied scenario. Then, with the help of this hypergraph, we make another step to put forward an IHG-based 3-dimensional matching (IHG-3DM) resource allocation protocol with a greedy 3DM algorithm and an iterative 3DM algorithm. As a consequence, the network throughput is significantly improved with the help of our proposed IHG-3DM resource allocation protocol for the investigated NOMA-integrated V2X communications, which is verified by the simulation results.

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.

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.

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.

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).

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.

The fifth generation (5G) mobile communication system is regard as a key enabler in promoting the deployment of Internet of Things (IoT), which is accompanied by the increasing service demands such like high data rate, enormous connection, and low latency. To meet these demands, network slicing has been envisioned as an efficient technology to customize infrastructures and allocate resources for 5G IoT services. However, due to various application backgrounds and ubiquitous social interactions of IoT services, the heterogeneous and social-driven resource requirement of users should be carefully assessed in resource allocation for the sliced 5G wireless network. In this paper, a novel nature-inspired wireless resource allocation scheme with slice characteristic perception is proposed, which comprehensively analyzes the properties of slices and converts them into a network profit model of resource utilization. Specifically, personalized service preferences and evolutionary interest relationships of users are exploited to model the complex and dynamic network environment with cellular automaton, and a biologically inspired allocation strategy of virtual wireless resource is proposed on the requirements of continuously updated user groups. Simulation results show that the proposed scheme achieves favorable resource utilization and low computational complexity, which favors the dynamic IoT slicing architecture and improves the efficiency and flexibility of resource allocation.

Three-dimensional (3D) multiple input and multiple output (3D-MIMO) with massive antennas is a key technology to achieve high spectral efficiency and user experienced data rate for the fifth generation (5G) mobile communication system. To implement 3D-MIMO in 5G system, practical constraints on the product design should be considered. This paper proposes a systematic design for the 3D-MIMO product by considering the restrictions of both base band and the hardware, including cost, size, weight, and heat dissipation. The design has been implemented for 2.6-GHz time-division duplex band, and field trials have been conducted for performance validation with practical intercell interference in commercial network. The trial results show that this 3D-MIMO design can meet the spectral efficiency requirement of the 5G enhanced mobile broadband services. The performance gain of 3D-MIMO varies with the traffic load. When the traffic load is heavy, 3D-MIMO can enhance the cell throughput by 4~6.7 times. When the traffic load is low, the performance gain of this 3D-MIMO design decreases. The results from field trial also show that the performance of 3D-MIMO degrades in mobility scenarios, where further enhancement on acquiring instant channel status information are necessary to improve the robustness of 3D-MIMO to mobility.

Supporting diversified rates for real-time communications will become possible and essential with the rapidly increasing transmission rates provided by the 4th generation (4G) mobile communication systems. In this paper, a novel wireless Quality of Service (QoS) scheme suitable for broadband CDMA packet cellular systems with adaptive modulation coding is proposed and its characteristics are described. The proposed QoS scheme comprises several control factors laid on the MAC and RRC layers, and can be harmonized with IP-QoS. Two important control factors are proposed: radio-condition-aware admission control and resource allocation reflected multistage scheduling. Computer simulations and testbed experiments indicate that by using the radio-condition-aware admission control, stable and guaranteed service can be provided to real-time users regardless of the interference and the variation in the location of the mobile station. Moreover, resource allocation reflected multistage scheduling maintains guaranteed rates for real-time users and provides high resource utilization efficiency for best-effort users. Consequently, by using the proposed wireless QoS scheme, it is possible to provide users with high quality and diversified real-time services, on a packet based radio network for enhanced 3G and beyond.

The deployment of small cells with carrier aggregation (CA) is a significant feature of fifth generation (5G) mobile communication systems which could be characterized by the multi-dimensional heterogeneity on their diversified requirements upon different resources. Taking the heterogeneity into account, we consider here a joint optimization problem wherein multiple kinds of resources are concurrently allocated to optimize the system throughput utility while enhancing the network energy efficiency (EE) and maintaining the system stability. Especially, for the high-dimensional non-deterministic polynomial (NP)-hard allocation problem embedded, we conduct a mathematical programming model involving nonlinear integer constraints to seek the long-term stable utility on throughput and introduce an iterative optimal modulation and coding scheme-based (optimal MCS-based) heuristic algorithm as an effective solver. In addition, as data traffic and channel condition will be time-varying in the real world, an admission control based on the Lyapunov technique that requires no prior knowledge on channel information is proposed to reduce the system overhead. Finally, not only the performance bound is derived in theory, but also the numerical experiments are conduced to reveal its characteristics with respect to the system parameter V and the EE requirement.

Long Term Evolution (LTE) is the preliminary version of a fourth generation (4G) mobile communication system. Its aim is to support different services with high data rates and strict Quality of Experience (QoE) requirements of users. The main aim of this study is to present a prediction model based on Random Neural Networks (RNNs) for objective, non-intrusive prediction of video quality over LTE for video applications. A three layer feed-forward RNN model with gradient descent training algorithm has been developed. This model uses a combination of objective parameters in the application and network layers, such as Content Type (CT), Sender Bit Rate (SBR), resolution size, Frame Rate (FR), codec, and packet loss rate (PLR). The video quality was predicted in terms of the Mean Opinion Score (MOS). The results show an approximate 50% increase in accuracy using this model, compared to previous models. LTE-Sim software has been used to generate different samples for testing and training RNN model.

A high linearity down-conversion mixer for the application of the fourth generation (4G) mobile communication systems is presented. The presented 2.3 to 5.8GHz broadband mixer adopts current-reused and bulk-controlled techniques. The linearized transconductor stage is composed of the CMOS ampliflers and the bulk-controlled compensation (BCC) transistors. The bulk-controlled voltage is applied to adjust the threshold voltage of the BCC transistor. Thus, the equivalent third-order intermodulation (IM3) term of the CMOS ampliflers and the BCC transistors can be mitigated so as to improve the linearity. Furthermore, the current-reused architecture enhances the conversion gain of the proposed mixer and compensates the loss caused by the shunt feedback matching network. The presented mixer consumes 4.8mA from a 1.5V power supply. The measurement results of the mixer exhibit the maximum power conversion gain of 11.3dB. The input third-order intercept point (IIP3) of 4.7dBm over the entire 2.3{5.8GHz band is observed.

Three dimensional (3D) Multiple Input and Multiple Output (MIMO) is one of the most promising techniques for the 5th generation (5G) mobile communication system. To support its research, the property of elevation angle in 3D channel model should be accurately modeled. Conventionally, 3D channel is modeled with an assumption that the mean elevation angle of multipaths is coincided with the line-of-sight (LOS) direction. In order to investigate its authenticity and give the reliable 3D channel model, extensive 3D multiple antenna field channel measurements with 100 MHz bandwidth are conducted in three typical scenarios, including outdoor to indoor(O2I), urban microcell (UMi) and urban macrocell (UMa). The statistical characteristics and parameters are extracted and analyzed based on the measurement data. It is found that the assumption holds in the LOS condition. However, for non-line-of-sight (NLOS) condition, a difference exists between the mean elevation angle and the direction connecting transmitter and receiver, which is defined as the elevation angle offset. Then, the eigenvalue distribution and capacity are compared between the reconstructed 3D channels with and without elevation angle offset. Results show that the performance of 3D channel with angle offset fits the measurement data better whereas that without angle offset is underestimated.