Abstract
The FCC and ETSI have allocated spectrum in the 5.9 GHz band for intelligent transportation systems. However, this spectrum supports short-range transmissions (up to 1000 m) and limited bandwidth (up to 75 MHz), which are not enough to meet the increasing demand for in-car infotainment services. In this paper, we propose a distributed routing protocol for vehicular ad hoc networks, where cognitive radio enabled vehicles (CRVs) dynamically share the TV-band channels. In the proposed protocol, CRVs jointly select relay nodes, channels, transmission powers, and transmission rates so that their total transmission rates are maximized while meeting their rate demands and power constraints. This selection process is carefully executed so that ongoing communications between primary radios (PRs) and between other CRVs are not disrupted. Once the relay nodes are selected, they continue to relay more messages as long as they stay in a predefined forwarding area. By doing so, the overhead for selecting relay nodes can be substantially reduced. Channels, powers, and rates are changed on a per-packet and per-hop basis so that the proposed protocol can efficiently adapt to spectrum dynamics. Simulation results show that our protocol increases the end-to-end network throughput by up to 250 % and decreases the end-to-end delay by up to 400 % compared with other geographical routing protocols.
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Notes
Non-contiguous channel access is adopted to new IEEE standards 802.11ac/af[2].
We refer to an OFDM subcarrier as a subcarrier, for brevity.
Several techniques have been proposed for control-channel selection. See [18] and the references therein.
We assume that the noise is a stationary and ergodic random process and its statistics can be measured a priori.
The value of 𝜖 should be carefully chosen to avoid fast fading effect
In real systems, more delay factors should be considered such as the inter-frame spacing, propagation delays, etc. These are ignored in the example for simplicity.
The codes can be obtained from the authors upon request.
References
Air interface for broadband wireless access systems. IEEE 802.16 Standard (2009)
Part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) specifications. Amendment 4: enhancements for very high throughput for operation in bands below 6 GHz. IEEE P802.11ac/D5.1 (2013)
Abbagnale A, Cuomo F (2010) Gymkhana: a connectivity-based routing scheme for cognitive radio ad hoc networks. In: Proceedings of the IEEE INFOCOM’10 conference
Becker P, Birtel M, Christmann D, Gotzhein R (2011) Black-burst-based quality-of-service routing (BBQR) for wireless ad-hoc networks. In: Proceedings of the IEEE NOTERE’11 conference
Boschetti M, Mingozzi A (2002) On the two-dimensional knapsack problem. IMA J Manag Math 13:95–119
Cesana M, Cuomo F, Ekici E (2011) Routing in cognitive radio networks: challenges and solutions. Ad Hoc Netw 9(3):228–248
Cheng G, Liu W, Li Y, Cheng W (2010) Joint on-demand routing and spectrum assignment in cognitive radio networks. In: Proceedings of the IEEE ICC’10 conference, pp 6499–6503
Chintalapudi K, Radunovic B (2012) WiFi-NC: WiFi over narrow channels. In: Proceedings of the USENIX NDSI’12 conference
Chowdhury K, Felice M (2009) Search: a routing protocol for mobile cognitive radio ad-hoc networks. Comput Commun 32(18):1983–1997
Fasolo E, Zanella A, Zorzi M An effective broadcast scheme for alert message propagation in vehicular ad hoc networks. In: Proceedings of the IEEE ICC ’06 conference, pp 11–15
FCC: Third memorandum opinion and order (2012) http://www.fcc.gov/topic/white-space
Ghafoor K, Bakar K, Lloret J, Khokhar R, Lee K (2013) Intelligent beaconless geographical routing for urban vehicular environments. Wirel Netw 19:345–362
Giordano S, Stojmenovic I, Blazevie L (2004) Position-based routing algorithms for ad hoc networks: a taxonomy. Ad Hoc Wirel Netw:103–136
Karp B, Kung H (2000) GPSR: Greedy perimeter stateless routing for wireless networks. In: Proceedings IEEE MobiCom conference
Kim J, Krunz M (2011) Spectrum-aware beaconless geographical routing protocol for mobile cognitive radio networks. In: Proceedings of the IEEE GLOBECOM ’11 conference
Lee K, Lee U, Gerla M (2010) Geo-opportunistic routing for vehicular networks. IEEE Commun. Mag 48:164–170
Li F, Wang Y (2007) Routing in vehicular ad hoc network: a survey. IEEE Veh. Technol Mag 2(2):12–22
Lo BF (2011) A survey of common control channel design in cognitive radio networks. ELSEVIER Phys Commun 4:26–39
Lochert C, Mauve M, Fubler H, Hartenstein H (2005) Geographic routing in city scenarios. ACM SIGMOBILE Mob Comput Commun Rev 9(1):69–72
Nzouonta J, Rajgure N, Wang G, Borcea C (2009) VANET routign on city roads using real-time vehicular traffic information. IEEE Trans Veh Technol 58(7):3609–3626
Rajbanshi R, Wyglinski A, Minden G (2006) An efficient implementation of NC-OFDM transceivers for cognitive radios. In: Proceedings of the EAI CROWNCOM ’06 conference
Ruhrup S, Kalosha H, Nayak A, Stojmenovic I (2010) Message-efficient beaconless georouting with guaranteed delivery in wireless sensor. IEEE/ACM Trans Netw 18(1):95–108
Sanchez J, Ruiz P, Marin-Perez R (2009) Beacon-less geographic routing made practical: challenges, design guidelines, and protocols. IEEE Commun Mag 47(8):85–91
Xie M, Zhang W, Wong K (2010) A geometric approach to improve spectrum efficiency for cognitive relay networks. IEEE Trans Wireless Commun 9(1):268–281
Zhu G, Akyildiz I, Kuo G (2008) STOD-RP: spectrum-tree based on-demand routing protocol for multi-hop cognitive radio networks. In: Proceedings of the IEEE GLOBECOM ’08 conference
Acknowledgments
This work was supported by NPRP grant # NPRP 4-1034-2-385 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.
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Kim, J., Krunz, M. Spectrum-aware Beaconless Geographical Routing Protocol for Cognitive Radio Enabled Vehicular Networks. Mobile Netw Appl 18, 854–866 (2013). https://doi.org/10.1007/s11036-013-0476-5
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DOI: https://doi.org/10.1007/s11036-013-0476-5