Probabilistic Rateless Multiple Access for Machine-to-Machine Communication

Future machine to machine (M2M) communications need to support a massive number of devices communicating with each other with little or no human intervention. Random access techniques were originally proposed to enable M2M multiple access, but suffer from severe congestion and access delay in an M2M system with a large number of devices. In this paper, we propose a novel multiple access scheme for M2M communications based on the capacity-approaching analog fountain code to efficiently minimize the access delay and satisfy the delay requirement for each device. This is achieved by allowing M2M devices to transmit at the same time on the same channel in an optimal probabilistic manner based on their individual delay requirements. Simulation results show that the proposed scheme achieves a near optimal rate performance and at the same time guarantees the delay requirements of the devices. We further propose a simple random access strategy and characterized the required overhead. Simulation results show the proposed approach significantly outperforms the existing random access schemes currently used in long term evolution advanced (LTE-A) standard in terms of the access delay.Comment: Accepted to Publish in IEEE Transactions on Wireless Communication

Development of a Random Time-Frequency Access Protocol for M2M Communication

This thesis focuses on the design and development of the random time-frequency access protocol in Machine-to-Machine (M2M) communication systems and covers different aspects of the data collision problem in these systems. The randomisation algorithm, used to access channels in the frequency domain, represents the key factor that affects data collisions. This thesis presents a new randomisation algorithm for the channel selection process for M2M technologies. The new algorithm is based on a uniform randomisation distribution and is called the Uniform Randomisation Channel Selection Technique (URCST). This new channel selection algorithm improves system performance and provides a low probability of collision with minimum complexity, power consumption, and hardware resources. Also, URCST is a general randomisation technique which can be utilised by different M2M technologies. The analysis presented in this research confirms that using URCST improves system performance for different M2M technologies, such as Weightless-N and Sigfox, with a massive number of devices. The thesis also provides a rigorous and flexible mathematical model for the random time-frequency access protocol which can precisely describe the performance of different M2M technologies. This model covers various scenarios with multiple groups of devices that employ different transmission characteristics like the number of connected devices, the number of message copies, the number of channels, the payload size, and transmission time. In addition, new and robust simulation testbeds have been built and developed in this research to evaluate the performance of different M2M technologies that utilise the random time-frequency access protocol. These testbeds cover the channel histogram, the probability of collisions, and the mathematical model. The testbeds were designed to support the multiple message copies approach with various groups of devices that are connected to the same base station and employ different transmission characteristics. Utilising the newly developed channel selection algorithm, mathematical model, and testbeds, the research offers a detailed and thorough analysis of the performance of Weightless-N and Sigfox in terms of the message lost ratio (MLR) and power consumption. The analysis shows some useful insights into the performance of M2M systems. For instance, while using multiple message copies improves the system performance, it might degrade the reliability of the system as the number of devices increases beyond a specific limit. Therefore, increasing the number of message copies can be disadvantageous to M2M communication performance

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

Enhancing Radio Access Network Performance over LTE-A for Machine-to-Machine Communications under Massive Access

The expected tremendous growth of machine-to-machine (M2M) devices will require solutions to improve random access channel (RACH) performance. Recent studies have shown that radio access network (RAN) performance is degraded under the high density of devices. In this paper, we propose three methods to enhance RAN performance for M2M communications over the LTE-A standard. The first method employs a different value for the physical RACH configuration index to increase random access opportunities. The second method addresses a heterogeneous network by using a number of picocells to increase resources and offload control traffic from the macro base station. The third method involves aggregation points and addresses their effect on RAN performance. Based on evaluation results, our methods improved RACH performance in terms of the access success probability and average access delay

Lightly synchronized Multipacket Reception in Machine-Type Communications Networks

Machine Type Communication (MTC) applications were designed to monitor and control elements of our surroundings and environment. MTC applications have a different set of requirements compared to the traditional communication devices, with Machine to Machine (M2M) data being mostly short, asynchronous, bursty and sometimes requiring end-to-end delays below 1ms. With the growth of MTC, the new generation of mobile communications has to be able to present different types of services with very different requirements, i.e. the same network has to be capable of "supplying" connection to the user that just wants to download a video or use social media, allowing at the same time MTC that has completely different requirements, without deteriorating both experiences. The challenges associated to the implementation of MTC require disruptive changes at the Physical (PHY) and Medium Access Control (MAC) layers, that lead to a better use of the spectrum available. The orthogonality and synchronization requirements of the PHY layer of current Long Term Evolution Advanced (LTE-A) radio access network (based on glsofdm and Single Carrier Frequency Domain Equalization (SC-FDE)) are obstacles for this new 5th Generation (5G) architecture. Generalized Frequency Division Multiplexing (GFDM) and other modulation techniques were proposed as candidates for the 5G PHY layer, however they also suffer from visible degradation when the transmitter and receiver are not synchronized, leading to a poor performance when collisions occur in an asynchronous MAC layer. This dissertation addresses the requirements of M2M traffic at the MAC layer applying multipacket reception (MPR) techniques to handle the bursty nature of the traffic and synchronization tones and optimized back-off approaches to reduce the delay. It proposes a new MAC protocol and analyses its performance analytically considering an SC-FDE modulation. The models are validated using a system level cross-layer simulator developed in MATLAB, which implements the MAC protocol and applies PHY layer performance models. The results show that the MAC’s latency depends mainly on the number of users and the load of each user, and can be controlled using these two parameters

Intelligent RACH Access strategies for M2M Traffic over Cellular Networks

This thesis investigates the coexistence of Machine-to-Machine (M2M) and Human-to-Human (H2H) based traffic sharing the Random Access Channel (RACH) of an existing cellular network and introduced a Q-learning as a mean of supporting the M2M traffic. The learning enables an intelligent slot selection strategy in order to avoid collisions amongst the M2M users during the RACH contest. It is also applied so that no central entity is involved in the slot selection process, to avoid tampering with the existing network standards. The thesis also introduces a novel back-off scheme for RACH access which provides separate frames for M2M and conventional cellular (H2H) retransmissions and is capable of dynamically adapting the frame size in order to maximise channel throughput. A Frame ALOHA for a Q-learning RACH access scheme is developed to realise collision- free RACH access between the H2H and M2M user groups. The scheme introduces a separate frame for H2H and M2M to use in both the first attempt and retransmissions. In addition analytical models are developed to examine the interaction of H2H and M2M traffic on the RACH channel, and to evaluate the throughput performance of both slotted ALOHA and Q-learning based access schemes. In general it is shown that Q-learning can be effectively applied for M2M traffic, significantly increasing the throughput capability of the channel with respect to conventional slotted ALOHA access. Dynamic adaptation of the back-off frames is shown to offer further improvements relative to a fixed frame scheme. Also the FA-QL-RACH scheme offers better performance than the QL-RACH and FB-QL-RACH scheme

Survey of Spectrum Sharing for Inter-Technology Coexistence

Increasing capacity demands in emerging wireless technologies are expected to be met by network densification and spectrum bands open to multiple technologies. These will, in turn, increase the level of interference and also result in more complex inter-technology interactions, which will need to be managed through spectrum sharing mechanisms. Consequently, novel spectrum sharing mechanisms should be designed to allow spectrum access for multiple technologies, while efficiently utilizing the spectrum resources overall. Importantly, it is not trivial to design such efficient mechanisms, not only due to technical aspects, but also due to regulatory and business model constraints. In this survey we address spectrum sharing mechanisms for wireless inter-technology coexistence by means of a technology circle that incorporates in a unified, system-level view the technical and non-technical aspects. We thus systematically explore the spectrum sharing design space consisting of parameters at different layers. Using this framework, we present a literature review on inter-technology coexistence with a focus on wireless technologies with equal spectrum access rights, i.e. (i) primary/primary, (ii) secondary/secondary, and (iii) technologies operating in a spectrum commons. Moreover, we reflect on our literature review to identify possible spectrum sharing design solutions and performance evaluation approaches useful for future coexistence cases. Finally, we discuss spectrum sharing design challenges and suggest future research directions