Abstract
In the future, technology will be hidden in the environment and invisible to the user but, at the same time, responsive and adaptive to user interaction and environmental variations [1]. For example, smart buildings will become aware of the presence of people and of their needs: thanks to this, temperature and light conditions will be adapted automatically for the best comfort and optimal power consumption. The realization of such a vision requires a technology that can sense, process and respond to external stimuli, both human and environmental, coming from many spots of a large environment, such as a room, a house or a whole building. An answer to such needs may come from Wireless Sensor Networks (WSNs. These are networks that consist of a large number of energy-autonomous nodes deployed into the environment to collect physical data. Each node is equipped with sensors, digital and analog processing units and a radio transceiver [2]. Physical parameters, such as temperature, sound, light conditions, etc., are sensed and processed by each node. The resulting information is transmitted from node to node and propagates through the network, until it is collected by a central data sink or used by the network itself in distributed algorithms. Dense networks, composed of hundreds or thousands of devices, are required to accurately monitor an environment. Consequently, each node must be extremely cheap to limit the cost of the network and make this technology economically feasible. Moreover, the nodes must be small enough to be hidden, in order to be invisible to users and not affect the surrounding environment.
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- 1.
Depending on the frequency of operation and the required performance, antennas can also be integrated on silicon [11].
- 2.
In the following, the expressions “time reference” and “frequency reference” are interchangeable.
- 3.
Equation (2.1) gives a sufficient condition for enabling communication among all nodes. However, nodes whose timeslots occur shortly after a synchronization beacon can, in principle, have a shorter T wu and consequently a lower power consumption. This case is not analyzed in this work. In the following it is implicitly assumed that T wu is the same for all nodes.
- 4.
For more details on synchronization, see Sect. 2.4.3.
- 5.
Equation (2.9) is not mathematically rigorous; it has been developed considering that n fa is the product of the number of decisions to be taken in a timeslot by ℙ fa and that the number of decisions depends on the difference between the duration of the timeslots and the time used for reception of the preamble caused by false alarms, i.e. \({\mathit{n}}_{fa} = {\mathbb{P}}_{fa}\frac{{T}_{wu}-{\mathit{n}}_{fa}{N}_{\mathit{p}r}/DR} {{T}_{d}}\).
- 6.
The repetition code is a coding scheme in which each data bit is transmitted multiple times over the channel.
- 7.
The power of the transmitted signal is limited by the peak power provided by the energy source and the power management system and the expected efficiency of the transmitter. Note that the spectral mask requirements are still met if less power than 1 mW is emitted and the assumed value is a practical upper bound.
- 8.
Transmitting a signal with higher peak power requires a transmitting chain and, in particular, a power amplifier with higher linearity. Since linearity and power efficiency of a transmitter are contrasting requirements [35], a modulation requiring a lower P peak and consequently a lower CF is preferred.
- 9.
The number of bits in the preamble is chosen large enough to ease the implementation of the synchronization algorithm. At the same time, the choice N pr = 100 does not affect sensibly the total power consumption (see Sect. 2.3.5).
- 10.
Note that in the following we compute the detected energy of only one sampling, but in case of PPM two samplings per frame are needed. The adopted simplification is possible thanks to the equivalence in terms of energy and BER performance of PPM and OOK.
- 11.
The factor 2 derives from the presence of frequency errors both in transmitter and receiver.
- 12.
Though the analysis was carried on with an AWGN channel, it must be noted that a margin for fading and obstruction has been considered in Sect. 2.4.2. Propagation through a multipath channel only affects the energy received for each pulse, since the delay between successive pulses is much higher than multipath delay expected by typical channel models. The effect of interferers is treated in the next section.
- 13.
Each packet has a duration of 366 μs and the delay between the first and second packet in the burst is 625 μs.
- 14.
The period is adapted to the QoS required for the audio link.
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Sebastiano, F., Breems, L.J., Makinwa, K.A.A. (2013). Fully Integrated Radios for Wireless Sensor Networks. In: Mobility-based Time References for Wireless Sensor Networks. Analog Circuits and Signal Processing. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3483-2_2
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