Performance of Radar and Communication Networks Coexisting in Shared Spectrum Bands

Recent technological advancements are making the use of compact, low-cost, low-power mm-wave radars viable for providing environmental awareness in a number of applications, ranging from automotive to indoor mapping and radio resource optimisation. These emerging use-cases pave the road towards networks in which a large number of radar and broadband communications devices coexist, sharing a common spectrum band in a possibly uncoordinated fashion. Although a clear understanding of how mutual interference influences radar and communications performance is key to proper system design, the core tradeoffs that arise in such scenarios are still largely unexplored. In this paper, we provide results that help bridge this gap, obtained by means of an analytical model and extensive simulations. To capture the fundamental interactions between the two systems, we study mm-wave networks where pulsed radars coexist with communications devices that access the channel following an ALOHA policy. We investigate the effect of key parameters on the performance of the coexisting systems, including the network density, fraction of radar and communication nodes in the network, antenna directivity, and packet length. We quantify the effect of mutual interference in the coexistence scenario on radar detection and communication network throughput, highlighting some non-trivial interplays and deriving useful design tradeoffs

Statistische Analyse der Performance-Minderung von Kfz-Radaren bei gegenseitiger Interferenz

Radargeräte gelten als robuste Sensoren zur Umgebungserfassung bei Fahrassistenzsystemen. Mit der zunehmenden Etablierung von aktiven Sicherheitssystemen wächst auch die Marktdurchdringung von Radargeräten. Hierdurch werden gegenseitige Störungen und damit verbundene Performanzeinbußen wahrscheinlicher. Gleichzeitig wachsen die Ansprüche an die Zuverlässigkeit der Radarsensoren infolge hochautomatisierter Fahrfunktionen. Existierende Methoden zur Modellierung von Interferenz werden der Komplexität und Vielfältigkeit moderner Kfz-Radargeräte häufig nicht mehr gerecht, da die konkreten Übertragungsmuster beteiligter Radargeräte nicht ausreichend in Berechnungen mit eingebunden werden und statistisch zufällige Randbedingungen außer Acht gelassen werden. In dieser Arbeit wird erstmals ein Modell vorgestellt, das statistische Analysen der Interferenz zwischen Kfz-Radarsensoren unter Beachtung statistisch zufälliger Übertragungszeiträume erlaubt. Der Einfluss der Übertagungsmuster der beteiligten Radargeräte auf die Anzahl und Eigenschaften der Einzelstörungen wird ebenso miteinbezogen wie deren Auswirkung auf die analoge und digitale Signalverarbeitung. Mithilfe dieses Modells werden die Auswirkungen konkreter Sendemuster-Parameter auf die Interferenz isoliert untersucht. In Schlüsselszenarien des automatisierten Fahrens werden in Abhängigkeit von Position und Anzahl der Störer statistische Untersuchungen bezüglich der Interferenz-bedingten Performanzeinbußen angestellt

Coverage and Rate of Joint Communication and Parameter Estimation in Wireless Networks

From an information theoretic perspective, joint communication and sensing (JCAS) represents a natural generalization of communication network functionality. However, it requires the re-evaluation of network performance from a multi-objective perspective. We develop a novel mathematical framework for characterizing the sensing and communication coverage probability and ergodic rate in JCAS networks. We employ a formulation of sensing parameter estimation based on mutual information to extend the notions of coverage probability and ergodic rate to the radar setting. We define sensing coverage probability as the probability that the rate of information extracted about the parameters of interest associated with a typical radar target exceeds some threshold, and sensing ergodic rate as the spatial average of the aforementioned rate of information. Using this framework, we analyze the downlink sensing and communication coverage and rate of a mmWave JCAS network employing a shared waveform, directional beamforming, and monostatic sensing. Leveraging tools from stochastic geometry, we derive upper and lower bounds for these quantities. We also develop several general technical results including: i) a generic method for obtaining closed form upper and lower bounds on the Laplace Transform of a shot noise process, ii) a new analog of H{\"o}lder's Inequality to the setting of harmonic means, and iii) a relation between the Laplace and Mellin Transforms of a non-negative random variable. We use the derived bounds to numerically investigate the performance of JCAS networks under varying base station and blockage density. Among several insights, our numerical analysis indicates that network densification improves sensing SINR performance -- in contrast to communications.Comment: 87 pages, 5 figures. Published in IEEE Transactions on Information Theor