Shunliang Mei

An adaptive medium access control mechanism for cellular based Machine to Machine (M2M) communication

This paper discusses the realization of Adaptive Traffic Load slotted MACA in cellular based M2M communication. Based on the statistic information of the channels occupancy rate, the base station estimates the traffic load and calculates the RTS transmission probability and broadcast to the members. By using the ATL S-MACA we control the access of the terminals to the system for high arrival rates. Thus maintain its throughput at 70.4%. As no carry sensing module is needed, the implementation of this protocol is not very complex and only requires the continue measurement of the traffic load. ATL S-MACA protocol is qualified to be adopted in the system where no carrier sensing module is available, like the cellular based M2M modules.

Stable enhancement for AODV routing protocol

Routing algorithm has been the challenge in the wireless ad-hoc network for a long time because of the quick mutability of the network topology introduced by the mobility of nodes. AODV is appealing for ad hoc networks as an efficient on-demand routing protocol because of the low routing overhead and high performance. As an optimization for the current AODV, a novel stable adaptive enhancement for AODV routing protocol was proposed in this paper, which considers joint route hop count, node stability and route traffic load balance as the route selection criteria. Comparing with AODV protocol, the new algorithm has better performance as shown with the simulations results.

Scalable Topology and Energy Management in Wireless Sensor Networks

In wireless sensor networks, energy conserving techniques are crucial to achieve satisfying network lifetime. One effective way to significantly reduce the energy consumption of sensors is using topology management mechanism, which periodically selects some nodes to build up the forwarding backbone and allow the others to sleep (turn off the radios) for energy conservation. In this paper, we propose backbone energy efficient sleeping (BEES) management scheme, which has two attractive characteristics: (i) the backbone size is scalable with practical requirements; (ii) the backbone nodes are evenly distributed, which implies that the backbone itself is energy efficient for routing tasks. Simulation experiments evaluate the performance of BEES by comparing it with two existing topology management schemes. The results demonstrate the advantages of BEES over the existing algorithms.

A Power-aware and Range-free Localization Algorithm for Sensor Networks

Power efficiency and accuracy are among the primary design requirements of the localization algorithms in wireless sensor networks. However, to the knowledge of the authors, there has been neither previous detailed study on the energy consumption of localization algorithms, nor previous algorithm that considers the power consumption as the main metric. In this paper, we propose a power-aware and range-free localization algorithm, LR-DV-hop algorithm, which can effectively reduce the communication overhead and energy consumption. It is shown in the simulation results that, our algorithm can save up to 50% power consumption of the classical DV-hop algorithm while achieve better localization accuracy

Synchronization in TDMA ad hoc network

The ad hoc network may play an important part in future wireless communication systems. However, system synchronization of the ad hoc network is a big challenge due to the lack of a fixed infrastructure and the dynamically changing topology. A novel self synchronization algorithm is proposed for the ad hoc network based on TDMA; the network topology structure information is gathered in some assigned time slots to build a connected domain set and broadcast the system synchronization messages over the whole network. The system time slot cost of synchronization is about 16.7%, and the probability of a node being successfully synchronized is higher than 95% in typical network environments, as shown by simulation.

Adaptive codebook for limited feedback MIMO system

In Multi-User MIMO system, full multiplexing gain relies on accurate channel knowledge provided at the transmitter, but usually it cannot be directly acquired by the transmitter. One solution is the limited feedback scheme where each user quantizes its channel with a fixed codebook and sends it back to the transmitter. There are two types of codebooks frequently discussed in IEEE 802.16e: 16e codebook and DFT codebook. Due to different design criterions, 16e codebook achieves a better performance in uncorrelated channel and DFT codebook is more suitable for correlated channel. Since the real environment is a combination of uncorrelated channel and correlated channel, we propose an adaptive codebook which adapt to different channel distribution. Our adaptive codebook is constructed with both 16e and DFT codebooks, where DFT codebook is employed to reconstruct the channel spatial correlation matrix and shift 16e codebook to fit the current channel. This adaptive codebook obviously outperforms both 16e and DFT codebooks in any channel distribution with only a negligible increase in overhead. Moreover, our adaptive codebook avoids complicated mathematic operation, which is very easy to be implemented in practice.

Packet Scheduling in Broadband Wireless Networks Using Neuro-Dynamic Programming

The design of future-generation broadband wireless network introduces a set of challenging technical issues. This paper focuses on the packet scheduling algorithms. The key difficulty of the problem lies in the high variability of wireless channel capacity and the unknown model of packet arrival process. We view the packet scheduling problem as a semi-Markov decision process (SMDP), and approximately solve the problem by using the methodology of neuro-dynamic programming (or reinforcement learning). The proposed algorithm, called neuro-dynamic programming scheduling (NDPS), employs a feature-based linear approximating architecture to produce a near optimal solution of the corresponding SMDP problem. Simulation experiment is carried out to demonstrate that NDPS can simultaneously achieve three performance objectives: (i) QoS differentiation and guarantee, (ii) high bandwidth utilization, and (iii) both short-term and long-term fairness.

Designing energy efficient routing scheme with delay constraint forwireless sensor networks

In this paper, we consider energy efficient routing with delay constraint in wireless sensor networks. Our study is motivated by the following observation. Relaying between nodes seems to consume less transmission power than communication with large distances. However, this well-known issue is not always true when there is an end-to-end delay constraint. Since relaying increases the hop count, transmission rate for each hop has to be raised to satisfy the latency demand. Additional energy cost for raising transmission rate will counteract the benefit from relaying. Therefore, hop count and transmission rate should be carefully set to conserve energy. We propose a Delay-constrained Energy Efficient Routing (DEER) scheme, which adaptively adjust hop count and transmission rate according to delay constraint. It is demonstrated by simulation that DEER outperforms traditional routing schemes.

Robust Power-Aware Routing in Wireless Sensor Networks with Special Concern about Localization Error

The power-aware geographic routing algorithms provide energy-efficient and scalable solutions for wireless sensor networks. However, to the knowledge of the authors, no previous work has analyzed the impacts of localization errors on energy consumption in the power-aware routing, and no solution for this problem has been brought forward. In this paper, the error distribution of the widely used MLE localization system is first analyzed. Then based on the knowledge of the error distribution, a robust routing algorithm is provided to mitigate the effects of the localization errors on the energy consumption. It is shown in the simulation results that our algorithm can reduce the extra energy consumption caused by the localization errors and improve the successful delivery rate

Optimization of Broadcasting Scheme for the CASoRT System

Content Aware Soft Real Time Media Broadcast (CASoRT) is a new solution for information service of cellular network. As the similar distribution of users interest, the data of same content may be accessed and retransmitted frequently in cellular network during certain period of time, which caused the dissipation of both energy and spectrum efficiency. With the development of Data Mining, the CASoRT system could discovers the users common interests and broadcast such content to users who may be interested in. With those users accessing the content locally, the poential retransmission could be avoided and thus it could save energy from carriers view while providing the same real time experience to the users. In this paper, we propose a set of algorithm for the optimization of broadcasting scheme for the CASoRT system to achieve more energy efficiency.