Building accurate radio environment maps from multi-fidelity spectrum sensing data

In cognitive wireless networks, active monitoring of the wireless environment is often performed through advanced spectrum sensing and network sniffing. This leads to a set of spatially distributed measurements which are collected from different sensing devices. Nowadays, several interpolation methods (e.g., Kriging) are available and can be used to combine these measurements into a single globally accurate radio environment map that covers a certain geographical area. However, the calibration of multi-fidelity measurements from heterogeneous sensing devices, and the integration into a map is a challenging problem. In this paper, the auto-regressive co-Kriging model is proposed as a novel solution. The algorithm is applied to model measurements which are collected in a heterogeneous wireless testbed environment, and the effectiveness of the new methodology is validated

Controllable radio interference for experimental and testing purposes in wireless sensor networks

Abstract—We address the problem of generating customized, controlled interference for experimental and testing purposes in Wireless Sensor Networks. The known coexistence problems between electronic devices sharing the same ISM radio band drive the design of new solutions to minimize interference. The validation of these techniques and the assessment of protocols under external interference require the creation of reproducible and well-controlled interference patterns on real nodes, a nontrivial and time-consuming task. In this paper, we study methods to generate a precisely adjustable level of interference on a specific channel, with lowcost equipment and rapid calibration. We focus our work on the platforms carrying the CC2420 radio chip and we show that, by setting such transceiver in special mode, we can quickly and easily generate repeatable and precise patterns of interference. We show how this tool can be extremely useful for researchers to quickly investigate the behaviour of sensor network protocols and applications under different patterns of interference, and we further evaluate its performance