Guan-Yu Lin

Overload control for Machine-Type-Communications in LTE-Advanced system

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.

Dynamic Auction Mechanism for Cloud Resource Allocation

We propose a dynamic auction mechanism to solve the allocation problem of computation capacity in the environment of cloud computing. Truth-telling property holds when we apply a second-priced auction mechanism into the resource allocation problem. Thus, the cloud service provider (CSP) can assure reasonable profit and efficient allocation of its computation resources. In the cases that the number of users and resources are large enough, potential problems in second-priced auction mechanism, including the variation of revenue, will not be weighted seriously since the law of large number holds in this case.

Network access for M2M/H2H hybrid systems: a game theoretic approach

Long Term Evolution-Advanced (LTE-A) is prospering as one of the promising mobile communication systems. In the near future, it is expected that in addition to traditional humanto- human (H2H) communications, an LTE-A system needs to support many applications with the technique of machine type communications (MTC), or machine-to-machine communications (M2M). Since M2M features a large number of devices, a mechanism to guarantee the performance of H2H and M2M in the random access procedure of LTE-A (RACH procedure) should be considered. However, little research provides dynamic RACH resource allocation approaches for H2H and M2M. In this paper, we propose a game-theoretic framework, which divides its random access resources into three groups: for H2H, for M2M, and for the hybrid usage. Under this framework, the Nash Equilibrium (NE) guarantees the system throughput by adaptively redistributing the traffic loading, and the NE can be approached rapidly even if the information of traffic loading is quite limited.

Estimation and Adaptation for Bursty LTE Random Access

With the potential to generate numerous connection requests, an explosive growth in the volume of data traffic and the number of mobile and machine-to-machine devices has drawn new attention to the radio access network. Surging random-access attempts cause not only severe preamble collisions but downlink resource shortage as well, thus degrading the performance of the random-access procedure. However, the effect of downlink resource shortage on system performance has yet to be comprehensively studied. In addition, most existing random-access contention resolution mechanisms sacrifice random-access channel (RACH) throughput for a high success probability, and thus, the price is that low-throughput mechanisms need a lot of time to deal with access attempts. In this paper, we evaluate the medium-access-control (MAC)-level performance for the four-step random-access procedure in Long-Term Evolution (LTE) systems, both with and without constrained downlink resources. Furthermore, we propose a novel RACH contention resolution scheme, i.e., the dynamic backoff (DB) scheme. DB can achieve high RACH throughput, yielding a high random-access success probability under various RACH overloaded scenarios.

Performance evaluation of radio access network overloading from machine type communications in LTE-A networks

Featuring massive number of devices, Machine Type Communications (MTC) poses great challenges for radio access network (RAN) with its overloading problem that has been aggressively addressed by 3GPP as an essential working item. In this article, we first introduce random access procedure in LTE-A. Then we address the issue of RACH overload coming from massive number of MTC devices. To resolve RAN overload, several easy-to-implement RAN level solutions are proposed. Based on simulation of MTC in Long Term Evolution- Advanced (LTE-A) architecture, we compare the overload resolution capability of different overload resolution mechanisms and conclude with observations for further solution design.

Reliable Multicast and Broadcast Mechanisms for Energy-Harvesting Devices

The technologies of energy harvesting enable wireless sensors to provide a slow but steady transmission rate with very low deployment cost. To efficiently (re)configure settings, transmit data, or update system information to a group of energy-harvesting devices, broadcast/multicast schemes should be carefully designed. Currently, two main challenges to reliable broadcast transmission are known as transmission error and energy deficiency. The former comes from nonperfect channel conditions, and the latter is a result of power shortage, causing devices to work abnormally due to energy exhaustion. Considering the two challenges, we propose an erasure-based broadcast scheme for an energy-harvesting network to guarantee reliable broadcast transmission. We address the tradeoff between reliability and throughput, and based on this, we propose three policies to determine the broadcast period for different performance requirements. Simulation results show that the proposed schemes and policies can significantly improve the performance of broadcast transmission based on energy harvesting characteristics.

Markov chain performance model for IEEE 802.11 devices with energy harvesting source

Research on energy harvesting networks has attracted an increasing attention lately. Nevertheless, few research of energy harvesting network follows the IEEE 802.11 protocol, whose medium access control (MAC) mechanism, called distributed coordination function (DCF), is based on the carrier sense multiple access with collision avoidance (CSMA/CA) algorithm and binary exponential random backoff. In this paper, we propose a modified DCF integrating the IEEE 802.11 MAC and the characteristic of device recharging model. A three-dimensional Markov chain is then constructed to evaluate the network performance of the modified DCF, such as throughput and delay. The proposed model addresses essential characteristics of an energy harvesting network and contributes to further study on MAC protocol in energy harvesting networks.

Context-Aware Dynamic Resource Allocation for Cellular M2M Communications

While the huge number of machine-to-machine (M2M) devices connects to the LTE system, the bursty random access attempts from them are potential to cause severe random access collisions and degrade the successful probability as well as delay of network connection establishment. To address this issue, current LTE spec has specified access class barring (ACB) and enhanced access barring (EAB), but both methods lack a contention detection method to decide when to activate it as well as a proper way to dynamically adjust the parameter. In this work, we first proposed a contention detection method that can work with current long-term evolution (LTE) standard and is easy to be implemented. To further improve the random access performance in dynamic world, we proposed a context-aware dynamic resource allocation (CADRA) mechanism, which is a two-phase method to resolve random access contention: Phase I for the estimation of random access attempts, and Phase II for resource allocation. By CADRA, high resource efficiency and low random access delay can be achieved without prior knowledge about random access arrival traffic, and thus this approach is competent in diverse applications and scenarios of Internet of Things (IoT). Simulation results show that the proposed contention detection method works great with ACB and EAB. Our proposed CADRA has good performance in resource efficiency and delay while satisfying success probability.

Auction-Based Random Access Load Control for Time-Dependent Machine-to-Machine Communications

Random access channel (RACH) contention issue has drawn great attention due to the prospering development of machine-to-machine (M2M) and Internet-of-Things (IoT) applications. Since a high preamble transmission rate is the direct cause of RACH contention, in this paper, we propose a two-stage scheme to control preamble transmission in multiple periods. In stage I, we design an auction method to balance and allocate the RACH transmission traffic among periods. In stage II, we propose an RACH attempt estimation method to control the preamble transmission rate decided by stage I. Through the two-stage scheme, we can efficiently handle a great number of random access request coming from diverse M2M applications.

A Distributed Multi-Channel Feedbackless MAC Protocol for D2D Broadcast Communications

In Device-to-Device (D2D) broadcast communications, the design of Medium Access Control (MAC) protocol is quite challenging since it is urged on alleviating data collision under the constraints of no feedback messages, no central coordination, and half-duplex transmission. We propose a multi-channel MAC protocol for data channel competition. Theoretical and simulation results show that this protocol resolves all channel collisions in only a few iterations. Moreover, the collision resolution time is dominated by the number of channels, rather than the number of D2D transmitters. Thus, even in scenarios with densely-distributed D2D devices, the proposed protocol can guarantee short collision resolution time.