What is the right model for wireless channel interference?

Abstract

Abstract-In wireless communications, the desired wireless signal is typically decoded by treating the sum of all the other ongoing signal transmissions as noise. In the networking literature, this phenomenon is typically abstracted using a wireless channel interference model. The level of detail in the interference model, evidently determines the accuracy of the results based upon the model. Several works in the networking literature have made use of simplistic interference models, e.g., fixed ranges for communication and interference, the capture threshold model (used in the ns2 network simulator), the protocol model, and so on. At the same time, fairly complex interference models such as those based on the SINR (signal-to-interference-and-noise ratio) have also been proposed and used. We investigate the impact of the choice of the interference model, on the conclusions that can be drawn regarding the performance of wireless networks, by comparing different wireless interference models. We find that both in the case of random access networks, as well as in the case of scheduled networks (where node transmissions are scheduled to be completely conflict-free), different interference models can produce significantly different results. Therefore, a lot of caution should be exercised before accepting or interpreting results based on simplified interference models. Further, we feel that an SINR-based model is the minimum level of detail that should be employed to model wireless channel interference in a networking context.

Engineering wireless mesh networks

“…As the additive interference model captures a more realistic interference relation, we use it as the benchmark and compare the interference range and capture threshold models against it. We have presented similar results in [7] for a network with nodes regularly deployed on a grid. Here we consider a scenario where 30 nodes are arbitrarily deployed and we report our results in Fig.…”

Caeer: Channel Assignment and Energy-Efficient Routing Protocol in Cognitive Radio Adhoc Network

“…Aravind Iyer et al introduced additive interference model [14] for wireless channel interference and carry out the capture threshold model, but it does not focus on the heterogeneity components of spectrum interference band. Therefore, in our interference model, we introduce the signal-to-interference-plus-noise ratio (SINR) model which captures the interference experienced by links in wireless network.…”

“…We assume a capture threshold of 10dB, NN is one and if the position of PU y is on the border of the circle, which is covered by PU x's transmission, the interference range will be equal R I = 1.77827R T [14].…”

On cooperative wireless relaying: A joint routing and scheduling flow-based framework

“…It was also shown in [14] and [10] that cross-layer optimization of routing and scheduling jointly with physical layer parameters (power and rate) provides a significant improvement in throughput over the case that does not include rate and power control. The significance of the use of the physical SINR-based interference model was discussed in [8].…”

“…The works of [5], [6] considered only a fixed selection of relay pairs for a stringbased network with no spatial reuse during scheduling. In [7], optimization frameworks were proposed for distributed networks, but they are based on a simple protocol interference model, the use of which is questioned in [8]. A joint routing and relay assignment problem was proposed in [9], however, this model is based on the use of multiple orthogonal channels for interference-free transmission.…”