The way radio interference changes over time and space in wireless networks has significant impact on system performance. Bettstetter and his team gained novel insight on such interference dynamics using tools from stochastic geometry. Expressions for interference correlation and link outage rates in multipath fading and relay channels were derived. Future research addresses the prediction of interference with the objective to improve system performance.
The management of interference has always been an essential building block in the design and performance analysis of wireless communication systems. Roughly speaking, interference occurs if the communication between a transmitter and a receiver is disturbed by additional devices transmitting on the same frequency band in the vicinity of the receiver. Interference may cause transmissions to fail and sent information to be lost. The handling of interference is done differently from technology to technology. The mature GSM, for example, tries to avoid interference completely by using reserved channels for each communication. Its successor UMTS allows interference but employs code division multiple access (CDMA), where multiple users are not separated in time or frequency but use different spreading codes. Wireless LANs sometimes avoid interference to a certain degree by reserving a «transmission floor» around a communicating pair of devices and employ retransmission protocols in case packets are lost. Newer technologies allow interference to a certain degree but mitigate it at the receiver with help of modern signal processing techniques and multiple antenna systems. In distributed ad hoc and sensor networks, where no dedicated control entities can regulate the access to the shared wireless medium, interference remains a performance-limiting factor, partly because it is subject to considerable uncertainty.
All interference management techniques require a suitable modeling and comprehensive understanding of the interference behavior. The stochastic modeling of interference is the topic of the research project «Dynamics of Interference in Wireless Networks» lead by Christian Bettstetter, who was awarded with a € 300,000 funding contract from the Austrian Science Fund (FWF) in 2012. He and his team at the University of Klagenfurt aim at gaining a deep understanding of how interference changes over time and space—they investigate the interference dynamics and rigorously analyze its impact on system performance.
A key challenge is to express the correlation of interference in terms of mathematical equations. «We succeeded in deriving expressions for the temporal correlation of the interference power in a variety of cases» Udo Schilcher, PostDoc researcher in Bettstetter’s team, says. The impact of temporal correlation can be illustrated with the example of a retransmission protocol that sends a message again if the intended receiver was not able to receive the message due to interference. «Immediate retransmission of unreceived data makes no sense if interference persists. A transmission is more likely to succeed under improved interference conditions. Our results on the coherence time of interference reveal how long a sender should wait in order to obtain improved conditions with high probability,» Schilcher explains.
To demonstrate this scenario, the impact of correlated interference on the packet delivery rate in a cooperative relay network was analyzed, in which the receiver obtains the same packet from two different devices at two different time instances, thus exploiting space-time diversity. It was found that «temporal and spatial characteristics of interference play a significant role in shaping the system performance.»
The team was also able to derive the link outage probability in a wireless network with Poisson distributed interferers and Nakagami fading caused by multipath propagation. From a more general perspective, interference functionals and a variant of the Campbell–Mecke theorem from stochastic geometry were found.
«The next big challenge will be the prediction of the interference level into the future, based on our improved understanding of interference dynamics,» Bettstetter concludes. The availability of interference prediction would be of great benefit for wireless communications, in a similar way many technologies benefit from channel prediction today. Two design directions are pursued: making use of models from stochastic geometry describing the spatio-temporal dynamics of interference and analyzing and extrapolating the statistics of interference measurements obtained in the past. The precision and computational complexity of interference predictors must be evaluated by rigorous mathematical analysis and real-world measurements.
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