Towards Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions

The ever-increasing number of resource-constrained Machine-Type Communication (MTC) devices is leading to the critical challenge of fulfilling diverse communication requirements in dynamic and ultra-dense wireless environments. Among different application scenarios that the upcoming 5G and beyond cellular networks are expected to support, such as eMBB, mMTC and URLLC, mMTC brings the unique technical challenge of supporting a huge number of MTC devices, which is the main focus of this paper. The related challenges include QoS provisioning, handling highly dynamic and sporadic MTC traffic, huge signalling overhead and Radio Access Network (RAN) congestion. In this regard, this paper aims to identify and analyze the involved technical issues, to review recent advances, to highlight potential solutions and to propose new research directions. First, starting with an overview of mMTC features and QoS provisioning issues, we present the key enablers for mMTC in cellular networks. Along with the highlights on the inefficiency of the legacy Random Access (RA) procedure in the mMTC scenario, we then present the key features and channel access mechanisms in the emerging cellular IoT standards, namely, LTE-M and NB-IoT. Subsequently, we present a framework for the performance analysis of transmission scheduling with the QoS support along with the issues involved in short data packet transmission. Next, we provide a detailed overview of the existing and emerging solutions towards addressing RAN congestion problem, and then identify potential advantages, challenges and use cases for the applications of emerging Machine Learning (ML) techniques in ultra-dense cellular networks. Out of several ML techniques, we focus on the application of low-complexity Q-learning approach in the mMTC scenarios. Finally, we discuss some open research challenges and promising future research directions.Comment: 37 pages, 8 figures, 7 tables, submitted for a possible future publication in IEEE Communications Surveys and Tutorial

Energy-efficient wireless communication

In this chapter we present an energy-efficient highly adaptive network interface architecture and a novel data link layer protocol for wireless networks that provides Quality of Service (QoS) support for diverse traffic types. Due to the dynamic nature of wireless networks, adaptations in bandwidth scheduling and error control are necessary to achieve energy efficiency and an acceptable quality of service. In our approach we apply adaptability through all layers of the protocol stack, and provide feedback to the applications. In this way the applications can adapt the data streams, and the network protocols can adapt the communication parameters

Location and resource management for quality of service provisioning in wireless/mobile networks

Wireless communication has been seen unprecedented growth in recent years. As the wireless network migrates from 2G to 2.5G and 3G, more and more high-bandwidth services have to be provided to wireless users. However, existing radio resources are limited, thus quality-of-service (QoS) provisioning is extremely important for high performance networKing In this dissertation, we focus on two problems crucial for QoS provisioning in wireless networks. They are location and resource management. Our research is aimed to develop efficient location management and resource allocation techniques to provide qualitative services in the future generations of wireless/mobile networks. First, the hybrid location update method (HLU) is proposed based on both the moving distance and the moving direction of mobile terminals. The signaling cost for location management is analyzed using a 2D Markov walk model. The results of numerical studies for different mobility patterns show that the HLU scheme outperforms the methods employing either moving distance or moving direction. Next, a new dynamic location management scheme with personalized location areas is developed. It takes into account terminal\u27s mobility characteristics in different locations of the service area. The location area is designed for each individual mobile user such that the location management cost is minimized. The cost is calculated based on a continuous-time Markov chain. Simulation results acknowledge a lower cost of the proposed scheme compared to that of some known techniques. Our research on the resource management considers the dynamic allocation strategy in the integrated voice/data wireless networks. We propose two new channel de-allocation schemes, i.e., de-allocation for data packet (DASP) and de-allocation for both voice call and data packet (DASVP). We then combine the proposed de-allocation methods with channel re-allocation, and evaluate the performance of the schemes using an analytic model. The results indicate the necessity of adapting to QoS requirements on both voice call and data packet. Finally, a new QoS-based dynamic resource allocation scheme is proposed which differentiates the new and handoff voice calls. The scheme combines channel reservation, channel de-allocation/re-allocation for voice call and packet queue to adapt to QoS requirements by adjusting the number of reserved channels and packet queue size. The superiority of the propose scheme in meeting the QoS requirements over existing techniques is proved by the experimental studies

Performance Analysis of Signaling Delay for Wireless Cellular Networks

In wireless cellular networks, signaling traffic such as location update, paging and handoff due to the user\u27s mobility takes a considerable portion of the total traffic load. In addition, the maximum allowable delays may be different among the signaling packets. In this paper, we present an analytical model for evaluating a total processing delay of signaling packets of wireless cellular networks, which integrates the delays of the radio channel and the processing delay at the wired portion. Through numerical examples, we show that priority processing is effective for reducing the handoff processing delays. We also evaluate the delay difference among cells according to their position within the location area, and the influence of number of terminals upon the processing delays

Performance Analysis of Signaling Delay for Wireless Cellular Networks

In wireless cellular networks, signaling traffic such as location update, paging and handoff due to the user\u27s mobility takes a considerable portion of the total traffic load. In addition, the maximum allowable delays may be different among the signaling packets. In this paper, we present an analytical model for evaluating a total processing delay of signaling packets of wireless cellular networks, which integrates the delays of the radio channel and the processing delay at the wired portion. Through numerical examples, we show that priority processing is effective for reducing the handoff processing delays. We also evaluate the delay difference among cells according to their position within the location area, and the influence of number of terminals upon the processing delays

Paging and Registration in Cellular Networks: Jointly Optimal Policies and an Iterative Algorithm

This paper explores optimization of paging and registration policies in cellular networks. Motion is modeled as a discrete-time Markov process, and minimization of the discounted, infinite-horizon average cost is addressed. The structure of jointly optimal paging and registration policies is investigated through the use of dynamic programming for partially observed Markov processes. It is shown that there exist policies with a certain simple form that are jointly optimal, though the dynamic programming approach does not directly provide an efficient method to find the policies. An iterative algorithm for policies with the simple form is proposed and investigated. The algorithm alternates between paging policy optimization and registration policy optimization. It finds a pair of individually optimal policies, but an example is given showing that the policies need not be jointly optimal. Majorization theory and Riesz's rearrangement inequality are used to show that jointly optimal paging and registration policies are given for symmetric or Gaussian random walk models by the nearest-location-first paging policy and distance threshold registration policies.Comment: 13 pages, submitted to IEEE Trans. Information Theor

Effective Capacity Analysis for Cognitive Networks under QoS Satisfaction

Spectrum sensing and dynamic spectrum access (DSA) techniques in cognitive radio networks (CRN) have been extensively investigated since last decade. Recently, satisfaction of quality-of-service (QoS) demands for secondary users (SU) has attracted great attention. The SU can not only discover the transmission opportunities, but also cognitively adapts the dynamic spectrum access strategies to its own QoS requirement and the environment variations. In this paper, we study how the delay QoS requirement affects the strategy on network performance. We first treat the delay-QoS in interference constrained cognitive radio network by applying the effective capacity concept, focusing on the two dominant DSA schemes: underlay and overlay. We obtain the effective capacity of the secondary network and determine the power allocation policies that maximize the throughput of the cognitive user. The underlay and overlay approaches may have their respective advantages under diverse propagation environment and system parameters. If the cognitive network can dynamically choose the DSA strategy under different environment, its performance could be further improved. We propose a selection criterion to determine whether to use underlay or overlay scheme under the given QoS constraint and the PUs’ spectrum-occupancy probability. Thus, the throughput of the CRN could be increased. Performance analysis and numerical evaluations are provided to demonstrate the effective capacity of CRN based on the underlay and the overlay schemes, taking into consideration the impact of delay QoS requirement and other related parameters