Fading (Radio)

Recent years have witnessed the deployments of
wireless sensor networks for mission-critical applications such
as battlefield monitoring and security surveillance. These appli-
cations often impose stringent Quality of Surveillance (QoSv)
requirements including low false alarm rate and short detection
delay. In practice, collaborative data fusion techniques that can
deal with sensing uncertainty and enable sensor collaboration
have been widely employed in sensor systems to achieve stringent
QoSv requirements. However, most previous analytical studies
on the surveillance performance of wireless sensor networks are
based on simplistic models (such as the disc model) that cannot
capture the stochastic and collaborative nature of sensing. In this
paper, we systematically analyze the fundamental relationship
between QoSv, network density, sensing parameters, and target
properties. The results show that data fusion is effective in
achieving stringent QoSv requirements, especially in the senarios
with low signal-to-noise ratios (SNRs). In contrast, the disc model
is only suitable when the SNR is sufficiently high. Our results
help understand the limitations of disc model and provide insights
into improving QoSv of sensor networks using data fusion.

Recent years have witnessed the deployments of
wireless sensor networks for mission-critical applications such
as battlefield monitoring and security surveillance. These appli-
cations often impose stringent Quality of Surveillance (QoSv)
requirements including low false alarm rate and short detection
delay. In practice, collaborative data fusion techniques that can
deal with sensing uncertainty and enable sensor collaboration have
been widely employed in sensor systems to achieve stringent QoSv
requirements. However, most previous analytical studies on the
surveillance performance of wireless sensor networks are based
on simplistic models (such as the disc model) that cannot capture
the stochastic and collaborative nature of sensing. In this paper,
we systematically analyze the fundamental relationship between
QoSv, network density, sensing parameters, and target properties.
The results show that data fusion is effective in achieving stringent
QoSv requirements, especially in the senarios with low signal-to-
noise ratios (SNRs). In contrast, the disc model is only suitable
when the SNR is sufficiently high. Our results help understand
the limitations of disc model and provide insights into improving
QoSv of sensor networks using data fusion.

Research in the wireless sensor networks field has been plagued by difficulties in realistic simulations. These difficulties are often the result of non-realistic assumptions which need to be removed from the mathematical models. Especially, radio propagation models are often simplified and do not take into consideration irregularities such as fading, shadowing, and temporal non-stationarity. In this paper, we investigate the effect of radio temporal irregularities on sensor deployment and sleep scheduling. We show that existing scheduling algorithms suppose that the sensor coverage range does not vary according to time, which is not true because the available energy decreases. We analyze the impact of this shortcoming on the performance of sleep scheduling algorithms and propose an alternative scheme that guarantees a uniform density distribution despite of the presence of radio temporal irregularities.

In present mobile radio systems, conventional FM techniques are used to transmit speech in its analog form. A number of digital schemes have been proposed in the past as an alternative. To overcome the effects of Rayleigh fades that appear in the received speech as noise bursts in the form of `pops' and `clicks', we propose, in this paper, packetizing speech and encoding the packets in an error-detecting code before transmitting them. If the receiver detects an error, it throws away the packet and requests the transmitter to retransmit the same packet. If the requested packet has not arrived in a given time period, the missed packets are replaced with zero amplitude values. The variable delays that packets are subjected to as a result of this procedure are smoothed out before packets are played back so that they all appear contiguous at the receiving end. The resulting improvement in the SNR at the receiving end depends, among other things, on the maximum delay we permit and the vehicle speed, and is achieved in addition to any improvement that is possible with a specially designed coder. For example, with 4 ms long packets and 12 ms of delay, the SNR improves by about 13 dB at a vehicle speed of 35 mph and 17 dB at 12 mph.

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=577064&tag=1

In a microwave mobile telecommunications system, a digital message must be transmitted several times to overcome the effects of Rayleigh fades that characterize this channel, and thus ensure a high probability that the message is received error-free. An analytic approach to an evaluation of the comparative performance of different transmission schemes in terms of the probability of a transmission failure is presented, and a basis for the design of an efficient scheme is provided. Some fade statistics that have been used are presented. The upper bounds are derived on probability of the transmission failure for three different schemes. The actual failure rates as determined in an experimental simulation are then shown for those schemes that the theoretical study predicts to be acceptable. It is shown that an efficient scheme for the Rayleigh fading channel is the block-protected one in which a message is transmitted four times, each transmission 4-ms long and spaced 4-ms apart. The spacing is obtained by interleaving a similar transmission of another message. The receiver discards a transmission if it fails the parity checks.

ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1622966

Research in the wireless sensor networks field has been plagued by difficulties in realistic simulations. These difficulties are often the result of non-realistic assumptions which need to be removed from the mathematical models. Especially, radio propagation models are often simplified and do not take into consideration irregularities such as fading, shadowing, and temporal non-stationarity. In this paper, we investigate the effect of radio temporal irregularities on sensor deployment and sleep scheduling. We show that existing scheduling algorithms suppose that the sensor coverage range does not vary according to time, which is not true because the available energy decreases. We analyze the impact of this shortcoming on the performance of sleep scheduling algorithms and propose an alternative scheme that guarantees a uniform density distribution despite of the presence of radio temporal irregularities.

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5587009

Research in the field of Wireless Sensor Networks (WSNs) has been plagued by difficulties in performing realistic simulations. For instance, most of the existing coverage optimization techniques presuppose that the region covered by a sensor node is a disc characterized by the radio transmission range. This assumption is rigorously false because of the propagation phenomena including fading and shadowing. This paper investigates the impact of these radio propagation phenomena on the coverage optimization strategy in a WSN. We rely on the log-normal shadowing model to represent the effect of the environmental features on the WSN performance. We propose a coverage model taking into account irregular radio propagation. We carry out a mathematical analysis to compute the average number of targets a sensor would detect under both perfect and irregular propagation conditions. We also conduct simulations to assess our random deployment model with respect to the existing strategies.

ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4917648