Wireless body area networks (WBANs) consist of small intelligent wireless sensors attached on or implanted in the body to collect vital biomedical data for providing a Continuous Health Monitoring System for diagnostic and therapeutic purposes. To fully exploit the benefits of WBANs the power consumption and sampling rate should be restricted to a minimum. The power usage can be minimised by optimising the features of multipath fading channels (MFCs) such as the number of arrival paths. That is why an improving of MFCs as well as a simple and generic channel model is inevitably required. With this in mind, compressed sensing (CS) theory, as a new sampling procedure, is employed to MFCs. Advance WBANs with the authors new model for MFCs based on CS theory will be able to deliver healthcare not only to patients in hospital and medical centres; but also in their homes and workplaces thus offering cost saving, and improving the quality of life. The authors simulation results illustrate 20% reduction for path loss and 10% for bit-error rate at gate way (GW). The simulation results also confirm that signal amplitude at GW increases by 25%, which will result in an increase, in the distance, between transmitter and receiver sensors.

The hidden-terminal problem and routing establishment or maintenance bring about a tremendous amount of energy consumption in multi-hop wireless sensor networks (WSNs). In this study, the authors propose a carrier sense multiple access with collision avoidance (CSMA/CA) scheme MultiCSMA for multi-hop WSNs adopting two strategies which refer to a novel hidden-terminal list algorithm to avoid the impact of hidden terminals and a parallel access scheme to dispense with taking the routing overhead into account. The accurate statistical performance metrics of throughput and delay of unsaturated, unacknowledged IEEE 802.15.4 beacon enabled networks for one-hop and two-hop scenarios are predicted based on Markov models adopting these two improved strategies, in which nodes are assumed to locate randomly over a circle plane according to Poisson distribution. Comprehensive simulations demonstrate that the analysis results match well with the simulation results, and delay performance of the authors schemes is superior to those of other schemes, whereas throughput is superior to others for relative higher node density.

In this study, a distributed traffic-aware routing scheme is proposed for a wireless sensor network with multiple sinks. In multi-sink networks, traffic moving towards one sink may congest that moving towards others. The algorithm proposed here considers the traffic of surrounding neighbours before jumping to any sink. This is accomplished by building for each single sink, a gradient field and using gradient-based search for routing. The gradient index of one node contains two parts. (i) The first represents the distance-cost to travel, based on routing over lossy link) proposed by an IETF working group. (ii) The second contains the implicit traffic delay carried by the current holding node. Gradient field is built in distributed way and proven to free from loops. In a simulation, the authors show that this method of building gradient field routes balances the shortest path and possible congestion made by sinks, especially in heavy traffic networks, thereby reducing the overall end-to-end delay.

Traditional routing protocols are no longer suitable for the energy harvesting-wireless sensor networks (EH-WSN), which is powered by the energy harvested from environment instead of batteries. Rather than minimising the energy consumption and maximising the network lifetime, the main challenge in EH-WSN is to maximise its working performance under energy harvesting constraints. In this study, the authors propose a centralised power efficient routing algorithm energy harvesting genetic-based unequal clustering-optimal adaptive performance routing algorithm (EHGUC-OAPR) which contains two parts: (i) energy harvesting genetic-based unequal clustering algorithm EHGUC and (ii) optimal adaptive performance routing algorithm (OAPR). First, the base station (BS) uses EHGUC algorithm to form clusters of unequal size and select associated cluster heads, in which the clusters closer to the BS have smaller size. Then, the BS adopts OAPR algorithm to construct an optimal routing among each cluster heads. The numerical results show that EHGUC-OAPR is not only well applied to EH-WSN, but also has a great improvement in network energy balance and data delivery ratio.

The emerging applications have imposed strong requirements, such as high processing capacity, low-power consumption, reduced size and many others, on the sensor-based systems. Owing to their balanced combination of flexibility and hardware performance, digital signal processors (DSPs) have become more and more popular used in sensor-based systems. Many DSPs have adopted very long instruction words (VLIW) style architecture, for its ability to greatly enhance instruction level parallelism. However, as VLIW codes are statically scheduled, the behaviour of VLIW architecture is dominated by the efficiency of its compiler. Single instruction multiple data (SIMD) instructions, which perform multiple operations in parallel on multiple data packed in registers, have been widely used in DSPs to meet the requirements of sensor-based systems. Although hand programming still yields the best performing SIMD codes, it is both time consuming and error prone. Advanced compiler techniques to automatically generate SIMD instructions, are under urgent demand. In this study, the authors proposed an SIMD code auto generation approach for VLIW architecture. It recognises candidates of operations in the intermediate representation, evaluates the possibility of grouping them into SIMD code, reconstructs the verified ones according to the cost model and finally generates the SIMD code. The authors have implemented this approach in the compiler of a VLIW DSP named Magnolia, which is designed for sensor-based systems. The results show that the authors’ approach is very efficient, and can largely enhance the performance.

Location is important for most wireless sensor network applications. A potential localisation method uses a mobile beacon instead of numerous static beacons. This method includes planning a beacon trajectory as a fundamental and interesting problem. Obstacles in practical scenarios often restrict the free locomotion of beacons. This study examines the obstacle-avoidance path-planning method, which consists of three stages. First, the network deployment region is partitioned into cells by adaptive cell decomposition, and the corresponding connectivity graph is constructed. Second, a modified max–min ant system algorithm is provided to obtain the approximate shortest global path that covers the connectivity graph. Finally, a sequence of concentric circles of adjustable radii is utilised as the local path within an obstacle-free cell. We prove that all sensor nodes deployed in obstacle-free cells can be localised by using the proposed path. Simulation results show that more than 90% of the sensor nodes in the obstacle-free region can be localised by using the given trajectory.

To minimise transmission completion time in energy-harvesting rechargeable communication systems, various transmission scheduling schemes have been proposed. However, they did not consider the issue where a transmitter may fail before completing the transmission. To resolve this issue, transmission scheduling for broadcasting with energy-harvesting switching transmitters is studied. The broadcasting communication system consists of two transmitters and two users. The transmitters harvest energy independently and work alternately. The transmission scheduling problem is formulated as minimising the transmission completion time, under the energy causality constraint, the data transmission constraint, and the transmitter switching constraint. Transmitter switching is addressed by proving that a transmitter should not stop transmission before switching to the other transmitter and the switching threshold should be zero. Then, an optimal transmission policy is proposed based on earlier works on rate region and the transmitter switching mechanism. The proposed optimal transmission policy can achieve a larger rate region than several kinds of suboptimal transmission policies.

The authors propose a novel relay augmentation strategy for extending the lifetime of a certain class of wireless sensor networks. In this class sensors are located at fixed and pre-determined positions and all communication takes place through multi-hop paths in a fixed routing tree rooted at the base station. It is assumed that no accumulation of data takes place along the communication paths and that there is no restriction on where additional relays may be located. Under these assumptions the optimal extension of network lifetime is modelled as the Euclidean k-bottleneck Steiner tree problem. Only two approximation algorithms for this NP-hard problem exist in the literature: a minimum spanning tree heuristic (MSTH) with performance ratio 2, and a probabilistic 3-regular hypergraph heuristic (3RHH) with performance ratio √3 + ɛ. The authors present a new iterative heuristic that incorporates MSTH and show through simulation that their algorithm performs better than MSTH in extending lifetime, and outperforms 3RHH in terms of efficiency.

This study presents a cooperative wideband spectrum-sensing technique based on the entropy of the received signal in the frequency domain. To enhance the efficiency of detection, multiple suspicious cognitive users are excluded from the network using generalised extreme studentised deviate test and sigma limit test. The performance of the proposed technique is compared with the energy detection technique under different channel environments. The simulation results demonstrate that the entropy detection method, with excluded suspicious users, has 9 dB improvement in performance compared to the energy detection technique in extremely low signal-to-noise ratio regime. This is a significant improvement for cognitive radio systems. The simulations were performed with false alarm probability and detection probability of 0.01 and 0.9, respectively. The hardware-in-the-loop simulation of the proposed algorithm is further carried out in the Xilinx Virtex-4 Field Programmable Gate Array.