H2-ARQ-relaying: spectrum and energy efficiency perspectives

In this paper, we propose novel Hybrid Automatic Repeat re-Quest (HARQ) strategies used in conjunction with hybrid relaying schemes, named as H2-ARQ-Relaying. The strategies allow the relay to dynamically switch between amplify-and-forward/compress-and-forward and decode-and-forward schemes according to its decoding status. The performance analysis is conducted from both the spectrum and energy efficiency perspectives. The spectrum efficiency of the proposed strategies, in terms of the maximum throughput, is significantly improved compared with their non-hybrid counterparts under the same constraints. The consumed energy per bit is optimized by manipulating the node activation time, the transmission energy and the power allocation between the source and the relay. The circuitry energy consumption of all involved nodes is taken into consideration. Numerical results shed light on how and when the energy efficiency can be improved in cooperative HARQ. For instance, cooperative HARQ is shown to be energy efficient in long distance transmission only. Furthermore, we consider the fact that the compress-and-forward scheme requires instantaneous signal to noise ratios of all three constituent links. However, this requirement can be impractical in some cases. In this regard, we introduce an improved strategy where only partial and affordable channel state information feedback is needed

Topology control and data handling in wireless sensor networks

Our work in this thesis have provided two distinctive contributions to WSNs in the areas of data handling and topology control. In the area of data handling, we have demonstrated a solution to improve the power efficiency whilst preserving the important data features by data compression and the use of an adaptive sampling strategy, which are applicable to the specific application for oceanography monitoring required by the SECOAS project. Our work on oceanographic data analysis is important for the understanding of the data we are dealing with, such that suitable strategies can be deployed and system performance can be analysed. The Basic Adaptive Sampling Scheduler (BASS) algorithm uses the statistics of the data to adjust the sampling behaviour in a sensor node according to the environment in order to conserve energy and minimise detection delay. The motivation of topology control (TC) is to maintain the connectivity of the network, to reduce node degree to ease congestion in a collision-based medium access scheme; and to reduce power consumption in the sensor nodes. We have developed an algorithm Subgraph Topology Control (STC) that is distributed and does not require additional equipment to be implemented on the SECOAS nodes. STC uses a metric called subgraph number, which measures the 2-hops connectivity in the neighbourhood of a node. It is found that STC consistently forms topologies that have lower node degrees and higher probabilities of connectivity, as compared to k-Neighbours, an alternative algorithm that does not rely on special hardware on sensor node. Moreover, STC also gives better results in terms of the minimum degree in the network, which implies that the network structure is more robust to a single point of failure. As STC is an iterative algorithm, it is very scalable and adaptive and is well suited for the SECOAS applications

Optimisation of relay placement in wireless butterfly networks

As a typical model of multicast network, wireless butterfly networks (WBNs) have been studied for modelling the scenario when two source nodes wish to convey data to two destination nodes via an intermediary node namely relay node. In the context of wireless communications, when receiving two data packets from the two source nodes, the relay node can employ either physical-layer network coding or analogue network coding on the combined packet prior to forwarding to the two destination nodes. Evaluating the energy efficiency of these combination approaches, energy-delay trade-off (EDT) is worth to be investigated and the relay placement should be taken into account in the practical network design. This chapter will first investigate the EDT of network coding in the WBNs. Based on the derived EDT, algorithms that optimize the relay position will be developed to either minimize the transmission delay or minimize the energy consumption subject to constraints on power allocation and location of nodes. Furthermore, considering an extended model of the WBN, the relay placement will be studied for a general wireless multicast network with multiple source, relay and destination nodes

A Cross-Layer Modification to the DSR Routing Protocol in Wireless Mesh Networks

A cross-layer modification to the DSR routing protocol that finds high throughput paths in WMNs has been introduced in this work. The Access Efficiency Factor (AEF) has been introduced in this modification as a local congestion avoidance metric for the DSR routing mechanism as an alternative to the hop count (Hc) metric. In this modification, the selected path is identified by finding a path with the highest minimum AEF (max_min_AEF) value. The basis of this study is to compare the performance of the Hc and max_min_AEF as routing metrics for the DSR protocol in WMNs using the OPNET modeler. Performance comparisons between max_min_AEF, Metric Path (MP), and the well known ETT metrics are also carried out in this work. The results of this modification suggest that employing the max_min_AEF as a routing metric outperforms the Hc, ETT, and MP within the DSR protocol in WMNs in terms of throughput. This is because the max_min_AEF is based upon avoiding directing traffic through congested nodes where significant packet loss is likely to occur. This throughput improvement is associated with an increment in the delay time due to the long paths taken to avoid congested regions. To overcome this drawback, a further modification to the routing discovery mechanism has been made by imposing a hop count limit (HCL) on the discovered paths. Tuning the HCL allows the network manager to tradeoff throughput against delay. The choice of congestion avoidance metric exhibits another shortcoming owing to its dependency on the packet size. It penalises the smaller packets over large ones in terms of path lengths. This has been corrected for by introducing a ModAEF metric that explicitly considers the size of the packet. The ModAEF metric includes a tuning factor that allows the operator determine the level of the weighting that should be applied to the packet size to correct for this dependence