Auctioning based Coordinated TV White Space Spectrum Sharing for Home Networks Saravana Manickam, Mahesh K. Marina Sofia Pediaditaki Maziar Nekovee University of Edinburgh Intel Labs Samsung Thursday, 11 July 13 1
TV White Spaces • “White Spaces” refer to areas High Power TV Broadcasts where the spectrum is unused by the licensed user • TV band: 470-790 MHz • Protection of incumbent users is of utmost importance • Favorable propagation characteristics motivates several use cases • Rural Broadband • Hot-spot Coverage • In-home Broadband • In-home Multimedia White Spaces where the spectrum • Machine to Machine can be reused by low power devices Thursday, 11 July 13 2
White Space Database Assisted Access • Database discovery • Receives channel usage parameters based on its location from a WSDB it chooses. • Leverage the WSDB for interference aware coordinated TVWS sharing among secondary users Thursday, 11 July 13 3
Spectrum Sharing among Home Networks HWSN • Secondary users are Home Geolocation Spectrum Database Manager White Space Networks in our context Broadband Provider • TVWS access point obtains spectrum on behalf of in-home WSDs • Spectrum Manager allocates TVWS channels to HWSNs considering availability, usage by other WSDs, spectrum demand, and interference among WSDs Thursday, 11 July 13 4
Micro Auction based Spectrum Sharing • We propose the use of short term auctions for coordinating spectrum among secondary users • Key Considerations • Primary objective: Efficient Outcome • Truthful/Strategy-Proof • High Revenue • Low Computational Complexity • Efficient Spectrum Utilization Thursday, 11 July 13 5
Why not traditional auction schemes ? A: 2, 3 V: 8, 6, 2 D A: 2, 3 A: 1, 2 A: 1, 2, 3 V: 13, 8, 6 V: 18, 16, 4 V: 12, 10, 6 A C E B • Channel Re-use A: 1, 2, 3 V: 14, 12, 10 • Channel Sharing • Heterogeneous Channel Availability • Marginal Valuations Thursday, 11 July 13 6
VERUM : An online multi-unit truthful iterative auction Geolocation Database Demand Increment Round Price Exists ? Yes No Available Channels Spectrum Start of New Assign Clinched Manager Epoch Channels No of Channels HWSNs B D Announce Round Final Price Assignment A C E • If the aggregate demand of a HWSN’s neighbors is less than the number of channels available at that HWSN, then the difference is “clinched” by the HWSN. Thursday, 11 July 13 7
VERUM : An online multi-unit truthful iterative auction A: 2, 3 V: 8, 6, 2 D A: 2, 3 A: 1, 2 A: 1, 2, 3 V: 13, 8, 6 V: 18, 16, 4 V: 12, 10, 6 A C E B A: 1, 2, 3 V: 14, 12, 10 Thursday, 11 July 13 8
VERUM : An online multi-unit truthful iterative auction Round Price: 2 2 A: 2, 3 V: 8, 6, 2 D A: 2, 3 A: 1, 2 A: 1, 2, 3 3 V: 13, 8, 6 V: 18, 16, 4 V: 12, 10, 6 A C E 3 3 B 3 A: 1, 2, 3 V: 14, 12, 10 Thursday, 11 July 13 9
VERUM : An online multi-unit truthful iterative auction Round Price: 6 1 A: 2, 3 V: 8, 6, 2 D A: 2, 3 A: 1, 2 A: 1, 2, 3 2 V: 13, 8, 6 V: 18, 16, 4 V: 12, 10, 6 A C E 2 2 B 3 A: 1, 2, 3 V: 14, 12, 10 • Since demand of D is one where as two channels are available at E, a channel is “ clinched ” by E at price 6 Thursday, 11 July 13 10
VERUM : An online multi-unit truthful iterative auction Round Price: 8 0 A: 2, 3 V: 8, 6, 2 D A: 2, 3 A: 1, 2 A: 1, 2, 3 1 V: 13, 8, 6 V: 18, 16, 4 V: 12, 10, 6 A C E 2 2 B 3 A: 1, 2, 3 V: 14, 12, 10 • E clinches another channel at price 8, as demand of D reduces to zero. Thursday, 11 July 13 11
VERUM : An online multi-unit truthful iterative auction Round Price: 12 0 A: 2, 3 V: 8, 6, 2 D A: 2, 3 A: 1, 2 A: 1, 2, 3 1 V: 13, 8, 6 V: 18, 16, 4 V: 12, 10, 6 A C E 2 0 B 1 A: 1, 2, 3 V: 14, 12, 10 • C clinches a channel as the aggregate demand of C’s neighbors (A, B, and D) is two, where as three channels are available at C Thursday, 11 July 13 12
VERUM : An online multi-unit truthful iterative auction Round Price: 13 0 A: 2, 3 V: 8, 6, 2 D A: 2, 3 A: 1, 2 A: 1, 2, 3 0 V: 13, 8, 6 V: 18, 16, 4 V: 12, 10, 6 A C E 2 0 B 1 A: 1, 2, 3 V: 14, 12, 10 • B and C clinch a channel each at price 13 Thursday, 11 July 13 13
VERUM : An online multi-unit truthful iterative auction A: 2, 3 V: 8, 6, 2 D A: 2, 3 A: 1, 2 A: 1, 2, 3 V: 13, 8, 6 V: 18, 16, 4 V: 12, 10, 6 A C E B A: 1, 2, 3 V: 14, 12, 10 • Final allocations are, HWSN A wins one channel, B and C win two channels each. • The channels are allocated using a greedy algorithm Thursday, 11 July 13 14
VERUM : How is it different from existing schemes ? • We compare VERUM against VERITAS and SATYA , two existing truthful, efficient auction schemes • To preserve truthfulness, they employ complex pricing schemes that realize Vickrey pricing • VERITAS does not support channel sharing, heterogeneous channel availability, and marginal valuations • SATYA supports channel sharing, heterogeneous channel availability and marginal valuation, but is only polynomial under certain restrictions Thursday, 11 July 13 15
VERUM : How is it different from existing schemes ? 60 80 55 ����������������������������� ����������������������������� 70 50 % Reduction in Spectrum Utilization % Reduction in Revenue ����������������������������� ����������������������������� 45 ������������������������������� 60 ������������������������������� 40 50 35 30 40 25 30 20 15 20 10 10 5 0 0 100 400 600 800 1000 1200 1400 1600 1800 2000 40 45 50 55 60 65 70 75 80 85 90 95 100 Average Demand (%) Number of HWSNs • We formulate the revenue maximizing spectrum allocation problem for both exclusive use and shared use as an integer linear program and solve it using Gurobi solver for comparison • SATYA has a lower revenue due to channel sharing opportunities lost due to bucketing and ironing. Thursday, 11 July 13 16
VERUM : How is it different from existing schemes ? 400,000 400,000 ������������������������� ����������������������� ������������������������������� 350,000 350,000 ����������������������� ����������������������������� ������������������������� ����������������������������� 300,000 300,000 ������������������������������� 250,000 250,000 Revenue Revenue 200,000 200,000 150,000 150,000 100,000 100,000 50,000 50,000 0 0 100 400 600 800 1000 1200 1400 1600 1800 2000 100 400 600 800 1000 1200 1400 1600 1800 2000 Number of HWSNs Number of HWSNs • The higher revenue in the urban scenario is due to lower density of HWSNs resulting in higher channel reuse. Thursday, 11 July 13 17
Conclusions • Interference-aware coordinated TVWS spectrum sharing framework for home networks that relies on short-term auctions and leverages the geolocation database to additionally keep track of secondary use of TVWS spectrum. • We have developed an online multi-unit auction mechanism VERUM that is truthful and efficient. Thursday, 11 July 13 18
Reference S. Manickam, M. Marina, S. Pediaditaki, and M. Nekovee. Auctioning based Coordinated TV White Space Spectrum Sharing for Home Networks. arXiv CoRR abs/1307.0962 R. Murty, R. Chandra, T. Moscibroda, and P . Bahl. SenseLess: A Database-Driven White Spaces Network. IEEE Transactions on Mobile Computing, 11(2), Feb 2012 X. Zhou, S. Gandhi, S. Suri, and H. Zheng. eBay in the Sky: Strategy-Proof Wireless Spectrum Auctions. In Proc. ACM MobiCom, 2008. Thursday, 11 July 13 19
Thank you ! Saravana Manickam, R.S.Manik@ed.ac.uk Thursday, 11 July 13 20
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