The future wireless Fifth Generation (5G) communication network required a higher bandwidth in order to achieve greater data rate. It will be largely characterized by small cell deployments, typically in the range of 200 meters of radius/cell, at most. The implementation of small size networks delivers various advantages such as high data rate and low signal delay. However, it also suffers from various issues such as inter-cell, intra-cell, and inter-user interferences. This paper discusses the issues related to interference management for 5G network from the perspective of Heterogeneous Network and Device-to-Device communication, by using enabling techniques, such as Inter-cell Interference Coordination, Coordinated Multipoint, and Coordinated Scheduling. Furthermore, several pertinent issues have been critically reviewed focusing on their methodologies, advantages and limitations along with the future work. Future directions proposed by the 3rd Generation Partnership Project for interference mitigation has also been outlined. This review will act as a guide for the researchers to comprehend various existing and emerging enabling interference mitigation techniques for further exploration and smooth implementation of 5G wireless network.

Interference management issues for the future 5G network: a review

In industrial Internet of Things (IIoT) applications for smart manufacturing system, efficient allocation of the carrier and computing resources is crucial. However, existing resource assignment schemes in smart manufacturing system cannot provide timely provision of resources to the inherently dynamic and bursty user demands. To reflect real-time supply and demand for smart manufacturing resources, several research results on auction-style resource assignments have been introduced; however, security, privacy, and trust computing related issues are not actively discussed in the results. The resources should be assigned to devices according to the system policy, which depends on the information provided by IIoT devices. If there are any resource demanding devices, they can report manipulated malicious information for their own interest to obtain more resources. That is, the smart manufacturing system may be vulnerable due to selfish smart manufacturing devices’ behaviors. This reduces the efficiency of the entire system and moreover ceases the plant-wide process. While many research contributions related to the trust computing aim at detecting malicious nodes, this paper presents a novel view of trust computing by showing why devices inside the smart manufacturing system have to act honestly. In this paper, a Vickrey–Clarke–Groves auction-based hierarchical trust computing algorithm is proposed for: 1) computing carrier resources required for wireless communication between IIoT devices and gateways and 2) distributing CPU resources for processing data at central processing controller. Last, simulation results demonstrate that the utilities of each participant are maximized when the IIoT devices and gateways are trustful.

Internet of Things for Smart Manufacturing System: Trust Issues in Resource Allocation

In face of the explosive surge of mobile data services, spectrum aggregation or carrier aggregation technology has been proposed to improve system throughput and spectrum efficiency (SE) by aggregating licensed and unlicensed spectrum bands. However, the system performances would be severely deteriorated by the channel access collision if the channel access and resource scheduling approaches are not coordinated among different networks in the same spectrum band. Therefore, in order to improve the system throughput and the SE, a fairness-based license-assisted access and resource scheduling scheme are designed for the coexisting systems, incorporating long term evolution-advanced and WiFi systems in the unlicensed band. The optimal sizes of the contention window in the proposed fairness-based channel access approach are obtained in terms of various density ratios between these two systems. Furthermore, a novel resource scheduling approach employing linear programming is proposed to maximize the utility function with the goal of improving the service experience of users and the SE with various spectrum qualities. The theoretical proofs and simulation results verify the enhanced performances of the proposed approaches in terms of key metrics, such as throughput, SE, delay, and packet loss ratio.

Design and Performance Analysis of a Fairness-Based License-Assisted Access and Resource Scheduling Scheme

Carrier aggregation has been introduced by 3rd Generation Partnership project (3GPP) in order to meet the IMT-Advanced requirements Using carrier aggregation, multiple component carriers with a different bandwidth, dispersed within intra or inter bands can be simultaneously utilised to provide higher data rates, better coverage and lower latency resulting a better user experience However, carrier aggregation functionality requires modification to the radio resource management function of the network In this paper, we propose an efficient resource allocation and link adaptation algorithm to support carrier aggregation functionality for downlink 5G LTE-Advanced (LTE-A) network We consider a non-guaranteed bit rate bearers (best effort traffic), which can be used for non realtime applications such as file downloads Most of the existing work considered resource allocation, component carrier selection and link adaptation as separate problems We define a joint radio resource management problem with carrier aggregation functionality and propose a sub-optimal solution with a low computational complexity Simulation results show clearly that our algorithm outperforms state-of-the-art algorithms

A joint resource allocation and link adaptation algorithm with carrier aggregation for 5G LTE-Advanced network

Due to recent developments in the cellular communication system, stochastic process implementation is necessary. The cellular communication system exhibits random patterns in various domains, thereby compelling the utilization of stochastic processes to achieve an optimal output. User behaviors with respect to the variable geographical pattern, population density, architecture, data usage, and mobility over various cells are random in nature. Therefore, the stochastic-geometry-based Poisson point process (PPP) technique can be implemented to accurately analyze these random processes in device-to-device (D2D)-based cooperative cellular networks. The stochastic modeling entails the consideration of transmitters and receivers as the elements of stochastic point processes. The hexagonal method is not applicable for the implementation of heterogeneous network topologies, as it is not suitable for topologies, in which the cell size is not fixed. Therefore, a randomly designed heterogeneous network uses stochastic geometry as a viable solution for predicting the probabilistic parameters, including the cell interference, load distribution, coverage probability, base station (BS) mapping, and signal-to-interference-plus-noise ratio (SINR). Moreover, as a network architecture that is based on relay nodes (RNs), cellular and D2D users can be utilized in the domain of homogeneous random models. The associated phenomenon can be considered independent and Poisson. In this paper, the stochastic-geometric-based PPP approach is introduced for modeling the SINR, success probability, ergodic capacity, and outage probability for the D2D-enabled cooperative cellular network. The proposed PPP realistic model utilizes BS, RN, the cellular user (CU), and D2D user positioning method to design an interference-free network. The success probability, ergodic capacity, and outage probability for cellular and D2D users are used as metrics for evaluating the results with respect to various SINR threshold values and node densities. Moreover, the total success probability, ergodic capacity, and outage probability have been calculated for various multiple-input-multiple-output (MIMO) antenna configurations to validate the results. The results confirmed that the proposed PPP model approach outperforms the grid model and conventional multi-antenna ultra-dense network (UDN) approaches.

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A Stochastically Geometrical Poisson Point Process Approach for the Future 5G D2D Enabled Cooperative Cellular Network

In long term evolution-advanced (LTE-A) networks, the carrier aggregation technique is incorporated for user equipments (UEs) to simultaneously aggregate multiple component carriers (CCs) for achieving higher transmission rate. Many research works for LTE-A systems with carrier aggregation configuration have concentrated on the radio resource management problem for downlink transmission, including mainly CC assignment and packet scheduling. Most previous studies have not considered that the assigned CCs in each UE can be changed. Furthermore, they also have not considered the modulation and coding scheme constraint, as specified in LTE-A standards. Therefore, their proposed schemes may limit the radio resource usage and are not compatible with LTE-A systems. In this paper, we assume that the scheduler can reassign CCs to each UE at each transmission time interval and formulate the downlink radio resource scheduling problem under the modulation and coding scheme constraint, which is proved to be NP-hard. Then, a novel greedy-based scheme is proposed to maximize the system throughput while maintaining proportional fairness of radio resource allocation among all UEs. We show that this scheme can guarantee at least half of the performance of the optimal solution. Simulation results show that our proposed scheme outperforms the schemes in previous studies.

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Hong-Sheng Liao

Papers

An Efficient Downlink Radio Resource Allocation with Carrier Aggregation in LTE-Advanced Networks