Performance modelling and analysis of multiple coexisting IEEE 802.15.4 wireless sensor networks

With the features of low-power and flexible networking capabilities IEEE 802.15.4 has been widely regarded as one strong candidate of communication technologies for wireless sensor networks (WSNs). It is expected that with an increasing number of deployments of 802.15.4 based WSNs, multiple WSNs could coexist with full or partial overlap in residential or enterprise areas. As WSNs are usually deployed without coordination, the communication could meet significant degradation with the 802.15.4 channel access scheme, which has a large impact on system performance. In this thesis we are motivated to investigate the effectiveness of 802.15.4 networks supporting WSN applications with various environments, especially when hidden terminals are presented due to the uncoordinated coexistence problem. Both analytical models and system level simulators are developed to analyse the performance of the random access scheme specified by IEEE 802.15.4 medium access control (MAC) standard for several network scenarios. The first part of the thesis investigates the effectiveness of single 802.15.4 network supporting WSN applications. A Markov chain based analytic model is applied to model the MAC behaviour of IEEE 802.15.4 standard and a discrete event simulator is also developed to analyse the performance and verify the proposed analytical model. It is observed that 802.15.4 networks could sufficiently support most WSN applications with its various functionalities. After the investigation of single network, the uncoordinated coexistence problem of multiple 802.15.4 networks deployed with communication range fully or partially overlapped are investigated in the next part of the thesis. Both nonsleep and sleep modes are investigated with different channel conditions by analytic and simulation methods to obtain the comprehensive performance evaluation. It is found that the uncoordinated coexistence problem can significantly degrade the performance of 802.15.4 networks, which is unlikely to satisfy the QoS requirements for many WSN applications. The proposed analytic model is validated by simulations which could be used to obtain the optimal parameter setting before WSNs deployments to eliminate the interference risks.

Gain switched multi-carrier transmitter and pilot tone based receiver for long reach access networks

A novel and cost effective long reach PON downlink scenario is proposed employing a multi-carrier transmitter and pilot tone aided direct detection at the receiver. Error free performance with QPSK and 50km transmission is presented. © 2012 OSA.

Modeling link adaptation algorithm for IEEE 802.11 wireless LAN networks

Link adaptation is a critical component of IEEE 802.11 systems. In this paper, we analytically model a retransmission based Auto Rate Fallback (ARF) link adaptation algorithm. Both packet collisions and packet corruptions are modeled with the algorithm. The models can provide insights into the dynamics of the link adaptation algorithms and configuration of algorithms parameters. It is also observed that when the competing number of stations is high, packet collisions can largely affected the performance of ARF and make ARF operate with the lowest date rate, even when no packet corruption occur. This is in contrast to the existing assumption that packet collision will not affect the correct operation of ARF and can be ignored in the evaluation of ARF. The work presented in this paper can provide guidelines on configuring the link adaptation algorithms and designing new link adaptation algorithms for future high speed 802.11 systems. © 2006 IEEE.

Shannon capacity of nonlinear communication channels

The exponentially increasing demand on operational data rate has been met with technological advances in telecommunication systems such as advanced multilevel and multidimensional modulation formats, fast signal processing, and research into new different media for signal transmission. Since the current communication channels are essentially nonlinear, estimation of the Shannon capacity for modern nonlinear communication channels is required. This PhD research project has targeted the study of the capacity limits of different nonlinear communication channels with a view to enable a significant enhancement in the data rate of the currently deployed fiber networks. In the current study, a theoretical framework for calculating the Shannon capacity of nonlinear regenerative channels has been developed and illustrated on the example of the proposed here regenerative Fourier transform (RFT). Moreover, the maximum gain in Shannon capacity due to regeneration (that is, the Shannon capacity of a system with ideal regenerators – the upper bound on capacity for all regenerative schemes) is calculated analytically. Thus, we derived a regenerative limit to which the capacity of any regenerative system can be compared, as analogue of the seminal linear Shannon limit. A general optimization scheme (regenerative mapping) has been introduced and demonstrated on systems with different regenerative elements: phase sensitive amplifiers and the proposed here multilevel regenerative schemes: the regenerative Fourier transform and the coupled nonlinear loop mirror.

A 10 Mb/s visible light communication system using a low bandwidth polymer light-emitting diode

In this paper we experimentally demonstrate a 10 Mb/s error free visible light communications (VLC) system using polymer light-emitting diodes (PLEDs) for the first time. The PLED under test is a blue emitter with ∼600 kHz bandwidth. Having such a low bandwidth means the introduction of an intersymbol interference (ISI) induced penalty at higher transmission speeds and thus the requirement for an equalizer. In this work we improve on previous literature by implementing a decision feedback equalizer, rather than a linear equalizer. Considering 7% and 20% forward error correction codes, transmission speeds up to ∼12 Mb/s can be supported.

Dual-polarization multi-band OFDM signals for next generation core networks

Dual-polarization multi-band orthogonal frequency-division multiplexing (DP-MB-OFDM) signals are optimized at data rates up to 500 Gb/s in dispersion compensation fiber (DCF)-free long-haul links. We compare different polarization crosstalk compensation techniques and explore the DP-MB-OFDM transmission distance limitations. In addition, the impact of the OFDM subcarrier number and high-level modulation format on the transmission performance are also investigated. Finally, a comparison is made between DP-MB-OFDM and the industrial solution of single-carrier DP quaternary phase-shift keying (DP-QPSK) at 1000 km.

Socio-economic vision graph generation and handover in distributed smart camera networks

In this article we present an approach to object tracking handover in a network of smart cameras, based on self-interested autonomous agents, which exchange responsibility for tracking objects in a market mechanism, in order to maximise their own utility. A novel ant-colony inspired mechanism is used to learn the vision graph, that is, the camera neighbourhood relations, during runtime, which may then be used to optimise communication between cameras. The key benefits of our completely decentralised approach are on the one hand generating the vision graph online, enabling efficient deployment in unknown scenarios and camera network topologies, and on the other hand relying only on local information, increasing the robustness of the system. Since our market-based approach does not rely on a priori topology information, the need for any multicamera calibration can be avoided. We have evaluated our approach both in a simulation study and in network of real distributed smart cameras.

Improved adaptivity and robustness in decentralised multi-camera networks

In this paper we present increased adaptivity and robustness in distributed object tracking by multi-camera networks using a socio-economic mechanism for learning the vision graph. To build-up the vision graph autonomously within a distributed smart-camera network, we use an ant-colony inspired mechanism, which exchanges responsibility for tracking objects using Vickrey auctions. Employing the learnt vision graph allows the system to optimise its communication continuously. Since distributed smart camera networks are prone to uncertainties in individual cameras, such as failures or changes in extrinsic parameters, the vision graph should be sufficiently robust and adaptable during runtime to enable seamless tracking and optimised communication. To better reflect real smart-camera platforms and networks, we consider that communication and handover are not instantaneous, and that cameras may be added, removed or their properties changed during runtime. Using our dynamic socio-economic approach, the network is able to continue tracking objects well, despite all these uncertainties, and in some cases even with improved performance. This demonstrates the adaptivity and robustness of our approach.

Energy hole mitigation through cooperative transmission in wireless sensor networks

The energy balancing capability of cooperative communication is utilized to solve the energy hole problem in wireless sensor networks. We first propose a cooperative transmission strategy, where intermediate nodes participate in two cooperative multi-input single-output (MISO) transmissions with the node at the previous hop and a selected node at the next hop, respectively. Then, we study the optimization problems for power allocation of the cooperative transmission strategy by examining two different approaches: network lifetime maximization (NLM) and energy consumption minimization (ECM). For NLM, the numerical optimal solution is derived and a searching algorithm for suboptimal solution is provided when the optimal solution does not exist. For ECM, a closed-form solution is obtained. Numerical and simulation results show that both the approaches have much longer network lifetime than SISO transmission strategies and other cooperative communication schemes. Moreover, NLM which features energy balancing outperforms ECM which focuses on energy efficiency, in the network lifetime sense.

ACARS:adaptive context - aware rate selection for DSRC in vehicular networks

Throughput plays a vital role for data transfer in Vehicular Networks which is useful for both safety and non-safety applications. An algorithm that adapts to mobile environment by using Context information has been proposed in this paper. Since one of the problems of existing rate adaptation algorithm is underutilization of link capacity in Vehicular environments, we have demonstrated that in wireless and mobile environments, vehicles can adapt to high mobility link condition and still perform better due to regular vehicles that will be out of communication range due to range checking and then de-congest the network thereby making the system perform better since fewer vehicles will contend for network resources. In this paper, we have design, implement and analyze ACARS, a more robust algorithm with significant increase in throughput performance and energy efficiency in the mist of high mobility of vehicles.

Cramer-Rao bound analysis of location estimation in multi-hop wireless sensor networks

Location estimation is important for wireless sensor network (WSN) applications. In this paper we propose a Cramer-Rao Bound (CRB) based analytical approach for two centralized multi-hop localization algorithms to get insights into the error performance and its sensitivity to the distance measurement error, anchor node density and placement. The location estimation performance is compared with four distributed multi-hop localization algorithms by simulation to evaluate the efficiency of the proposed analytical approach. The numerical results demonstrate the complex tradeoff between the centralized and distributed localization algorithms on accuracy, complexity and communication overhead. Based on this analysis, an efficient and scalable performance evaluation tool can be designed for localization algorithms in large scale WSNs, where simulation-based evaluation approaches are impractical. © 2013 IEEE.

Scaling the Advantages of Intra-channel Nonlinearity Compensation in Future Flexible Optical Networks

We report that, contrary to common perception, intra-channel nonlinearity compensation offers significant improvements of up to 4dB, in nonlinear tolerance (Q-factor), in a flexible traffic scenario, and further improvements with increasing local link dispersion, for an optical transport network employing flexible 28Gbaud PM-mQAM transponders.

Static, dynamic, and adaptive heterogeneity in distributed smart camera networks

We study heterogeneity among nodes in self-organizing smart camera networks, which use strategies based on social and economic knowledge to target communication activity efficiently. We compare homogeneous configurations, when cameras use the same strategy, with heterogeneous configurations, when cameras use different strategies. Our first contribution is to establish that static heterogeneity leads to new outcomes that are more efficient than those possible with homogeneity. Next, two forms of dynamic heterogeneity are investigated: nonadaptive mixed strategies and adaptive strategies, which learn online. Our second contribution is to show that mixed strategies offer Pareto efficiency consistently comparable with the most efficient static heterogeneous configurations. Since the particular configuration required for high Pareto efficiency in a scenario will not be known in advance, our third contribution is to show how decentralized online learning can lead to more efficient outcomes than the homogeneous case. In some cases, outcomes from online learning were more efficient than all other evaluated configuration types. Our fourth contribution is to show that online learning typically leads to outcomes more evenly spread over the objective space. Our results provide insight into the relationship between static, dynamic, and adaptive heterogeneity, suggesting that all have a key role in achieving efficient self-organization.

Scalable harmonization of complex networks with local controllers

Computational and communication complexities call for distributed, robust, and adaptive control. This paper proposes a promising way of bottom-up design of distributed control in which simple controllers are responsible for individual nodes. The overall behavior of the network can be achieved by interconnecting such controlled loops in cascade control for example and by enabling the individual nodes to share information about data with their neighbors without aiming at unattainable global solution. The problem is addressed by employing a fully probabilistic design, which can cope with inherent uncertainties, that can be implemented adaptively and which provide a systematic rich way to information sharing. This paper elaborates the overall solution, applies it to linear-Gaussian case, and provides simulation results.

Operational issues in access networks:past, present, and future

Future network operation will be influenced by business and ownership models and the regulatory environment as future superfast and flexible broadband networks emerge. This paper discusses the issues affecting operators and network operations as network evolution progresses.