Wireless cellular networks feature two emerging technological trends. The first is the direct Device-to-Device (D2D) communications, which enables direct links between the wireless devices that reutilize the cellular spectrum and radio interface. The second is that of Machine-Type Communications (MTC), where the objective is to attach a large number of low-rate low-power devices, termed Machine-Type Devices (MTDs) to the cellular network. MTDs pose new challenges to the cellular network, one if which is that the low transmission power can lead to outage problems for the cell-edge devices. Another issue imminent to MTC is the that can lead to overload of the radio interface. In this paper we explore the opportunity opened by D2D links for supporting MTDs, since it can be desirable to carry the MTC traffic not through direct links to a Base Station, but through a nearby relay. MTC is modeled as a fixed-rate traffic with an outage requirement. We propose two network-assisted D2D schemes that enable the cooperation between MTDs and standard cellular devices, thereby meeting the MTC outage requirements while maximizing the rate of the broadband services for the other devices. The proposed schemes apply the principles Opportunistic Interference Cancellation and the Cognitive Radio's underlaying. We show through analysis and numerical results the gains of the proposed schemes.
We propose a novel distributed random access scheme for wireless networks based on slotted ALOHA, motivated by the analogies between successive interference cancellation and iterative belief-propagation decoding on erasure channels. The proposed scheme assumes that each user independently accesses the wireless link in each slot with a predefined probability, resulting in a distribution of user transmissions over slots. The operation bears analogy with rateless codes, both in terms of probability distributions as well as to the fact that the ALOHA frame becomes fluid and adapted to the current contention process. Our aim is to optimize the slot access probability in order to achieve rateless-like distributions, focusing both on the maximization of the resolution probability of user transmissions and the throughput of the scheme. We evaluate the feasibility of cognitive machine-to-machine communication on cellular bands from engineering and business perspectives. We propose a hierarchical network structure for cognitive M2M communication, where cluster headers gather M2M traffic using cognitive radio and forward it to the cellular networks. This structure can resolve the congestion problem that arises in conventional M2M systems. We obtain the optimal network parameters that minimize congestion at the radio access network. In addition, we investigate the business value of cognitive M2M on cellular bands. Taking into account the network usage fee, service fee, and hardware production costs, we model the profit structure of M2M services and derive the condition under which the CR type of M2M communication is superior to conventional M2M communication. We find that the optimal network design parameters (i.e., the number of cluster headers and cluster size) for business value would be different from the parameters expected from an engineering point of view. We believe that cognitive M2M communication can be a good solution for dealing with excessive M2M traffic in cellular networks, in terms of technical feasibility and business opportunity. Machine-to-machine (M2M) communications emerge to autonomously operate to link interactions between Internet cyber world and physical systems. We present the technological scenario of M2M communications consisting of wireless infrastructure to cloud, and machine swarm of tremendous devices. Related technologies toward practical realization are explored to complete fundamental understanding and engineering knowledge of this new communication and networking technology front. Supporting trillions of devices is the critical challenge in machine-to-machine (M2M) communications, which results in severe congestions in random access channels of cellular systems that have been recognized as promising scenarios enabling M2M communications. 3GPP thus developed the access class barring (ACB) for individual stabilization in each base station (BS). However, without cooperations among BSs, devices within dense areas suffer severe access delays. To facilitate devices escaping from continuous congestions, we propose the cooperative ACB for global stabilization and access load sharing to eliminate substantial defects in the ordinary ACB, thus significantly improving access delays.  This paper describes issues related to one of the most significant challenges that 3GPP faces in supporting M2M communications over LTE: facilitating the support for low cost M2M devices. The paper considers the requirements for low cost M2M devices and the most significant contributors to device cost. System bandwidth is identified as being a significant cost contributor and backwards compatible approaches to reducing system bandwidth are identified. Cellular network based Machine-to-Machine (M2M) communication is fast becoming a market-changing force for a wide spectrum of businesses and applications such as telematics, smart metering, point-of-sale terminals, and home security and automation systems. In this paper, we aim to answer the following important question: Does traffic generated by M2M devices impose new requirements and challenges for cellular network design and management? To answer this question, we take a first look at the characteristics of M2M traffic and compare it with traditional smartphone traffic. We have conducted our measurement analysis using a week-long traffic trace collected from a tier-1 cellular network in the United States. We characterize M2M traffic from a wide range of perspectives, including temporal dynamics, device mobility, application usage, and network performance. Our experimental results show that M2M traffic exhibits significantly different patterns than smartphone traffic in multiple aspects. For instance, M2M devices have a much larger ratio of uplink to downlink traffic volume, their traffic typically exhibits different diurnal patterns, they are more likely to generate synchronized traffic resulting in bursty aggregate traffic volumes, and are less mobile compared to smartphones. On the other hand, we also find that M2M devices are generally competing with smartphones for network resources in co-located geographical regions. These and other findings suggest that better protocol design, more careful spectrum allocation, and modified pricing schemes may be needed to accommodate the rise of M2M devices. Increased attention has been drawn to machine type communication (MTC) lately, which represents important extension for user functionality in today's technologies, as well as an important potential for marketing expansion. GERAN studies over MTC has mainly focused on applications requiring low throughput and wide coverage such as smart meter, which could cause some impacts over normal data users if operating in a synchronous manner. This paper proposes a new methodology for studying the impact on signaling channels when mixture of synchronous and asynchronous traffic is present in the network. This is based on statistical analysis, considering signaling accessing attempts as driven by a Poisson process. In this approach successive random access attempts by the mobile stations are considered as well as the response on the network side. First implementation is held for GSM GPRS network, although generalization of the method for other technologies is possible. The simulated results show potential problems to be solved when a large number of synchronized users is present. Additionally, an analysis on the effects of the different levels of synchronization and the addition of extra signaling channels is included. Results also point out possible development paths that could be taken when designing new features to make networks more robust to synchronized traffic.  The random access methods used for support of machine-type communications (MTC) in current cellular standards are derivatives of traditional framed slotted ALOHA and therefore do not support high user loads efficiently. Motivated by the random access method employed in LTE, we propose a novel approach that is able to sustain a wide random access load range, while preserving the physical layer unchanged and incurring minor changes in the medium access control layer. The proposed scheme increases the amount of available contention resources, without resorting to the increase of system resources, such as contention sub-frames and preambles. This increase is accomplished by expanding the contention space to the code domain, through the creation of random access codewords. Specifically, in the proposed scheme, users perform random access by transmitting one or none of the available LTE orthogonal preambles in multiple random access sub-frames, thus creating access codewords that are used for contention. In this way, for the same number of random access sub-frames and orthogonal preambles, the amount of available contention resources is drastically increased, enabling the support of an increased number of MTC users. We present the framework and analysis of the proposed code-expanded random access method and show that our approach supports load regions that are beyond the reach of current systems. As Machine-Type-Communications (MTC) continues to burgeon rapidly, a comprehensive study on overload control approach to manage the data and signaling traffic from massive MTC devices is required. In this work, we study the problem of RACH overload, survey several types of RAN-level contention resolution methods, and introduce the current development of CN (core network) overload mechanisms in 3GPP LTE. Additionally, we simulate and compare different methods and offer further observations on the solution design. The need to deploy large number of wireless devices, such as electricity or water meters, is becoming a key challenge for any utility. Furthermore, such a deployment should be functional for more than a decade. Many cellular operators consider LTE to be the single long term solution for wide area connectivity serving all types of wireless traffic. On the other hand, GSM is a well-adopted technology and represents a valuable asset to build M2M infrastructure due to the good coverage, device maturity, and low cost. In this paper we assess the potential of GSM GPRS EDGE to operate as a dedicated network for M2M communications. In order to enable M2M-dedicated operation in the near future, we reengineer the GSM GPRS EDGE protocol in a way that requires only minor software updates of the protocol stack. We propose different schemes to boost the number of M2M devices in the system without affecting the network stability. We show that a single GSM cell can support simultaneous low-data rate connections (e. g. to smart meters) in the order of 104 devices.