1. UNIVERSITÀDEGLI STUDI DI ROMA “TOR VERGATA”Corso di Dottorato in Ingegneria delle Telecomunicazioni e Microelettronica “Dynamic frequency allocation in femtocells-based systems: algorithms and performance analysis” Advisor: Prof. Francesco Vatalaro Co Advisor: Prof. Franco Mazzenga Ph. D. candidate: Remo Pomposini

3. Problem statement

4. Dynamic Frequency Selection Algorithms

5. Results

6. Conclusions

7. Other activities

8. Publications2

10. Works on licensed band(s)

11. Typically supports 2 to 4 active mobile phones

12. Allows service providers to extend service coverage indoors

13. Extends BS to allow a simpler, self-contained deployment

14. Provides improvements to both coverage and capacity3

16. Cognitive radio

17. The wireless node changes its transmission and/or reception parameters to communicate efficiently

18. Executes active monitoring of several factors in the external and internal radio environment

19. Radio frequency spectrum

20. User behavior

21. Network state4

22. Problem statement and proposedsolutions 5

24. High bit-rate nodes

25. No accurate radio planning is possible

26. Small number of channels areavailable

27. Macro-to-femtointerference

28. can be avoided by allocating separated channels

29. Interferenceamongfemtocells

30. …even if a dedicated frequency band is allocated to the femtocell network.

31. harmful in highly dense HNB’s environments!

32. can compromise the opportunity of enjoying high data rate services.6

34. Noise power

35. Interference power on different bands

36. Interference can be reduced by:

37. Properly controlling the transmitted power (e.g. power control)

38. Change of femtocell operating frequencies

39. Idea: available operating frequencies for each femtocell can include all the bands allocated to the (several) mobile operators (e.g. mutual frequency exchange)7

41. Adoption of algorithms for intelligentfemto-BSs to dynamically set theiroperatingfrequencies

42. Algorithmsrequirements:

43. Shallconsider:

44. CooperatingFemtocells

45. No cooperationamongfemtocells

46. Algorithmsshall be simple to implement i.e. nodrasticalchangesto existing standard shall be required

47. Shall be based on the available data the single femtocell can measure locally8

49. Two operating modes of the femtocells needs to be considered:

50. Femtocell startup phase

52. connects to the own operator network

53. sets its RF parameters

54. core network assisted

55. self-setting RF parameters based on monitoring of the radio channels

56. self-optimization phase

57. Femtocell dynamically adapt its parameters to the changing environment conditions

59. Greedy DFS algorithm (GDFS):

60. femtocells are absolutelygreedy and aimtoimmediatelymaximizetheirSignal-to-InterferenceRatio (SIR) carelessofwhichoperatoroffers the lessinterferedchannel

61. Operator-oriented DFS algorithm (ODFS):

62. eachfemtocellusesitsown band until the QoSconditionisverified (SIR≥ρ0)

63. SIR11

65. If SIR > threshold

66. Decrease Ptx in order to reach the target quality level

67. Else

68. Increase Ptx up to Pmax

69. If Ptx>Pmax

70. Interference measurement on f1,f2,…,fN

71. If SIRop> threshold

72. Select the i-th frequency (belonging to own operator)

73. Else if SIRext > threshold

74. Select the j-th frequency (belonging to a different operator)

75. Else

76. Sensing mode

77. Sensing mode: programmed standby feature envisaged in order not to damage the other femtocells.

78. Since the interference conditions prevent the femtocell from transmitting, it temporarily disables transmission and just performs spectrum sensing.12

79. Results 13

81. Random

82. Regular grid

83. Perturbedgrid

84. Building

85. Maximumtrasmittedpower, Pmax = 20 dBm

86. DistanceFemtoBS-Terminal, DFBS-Terminal = 4 - 10 m

87. Outdoor pathlossexponent = 3.2

88. Indoor pathlossexponent = 2.8

89. Downlinktransmission direction isconsidered

90. Greedy data source

91. SINR threshold : 9,4 dB – 16,4 dB

92. Carrierfrequency, F = 1800MHz

93. Band frequencyspacing,Δfc = 10 MHz14

95. Femtocells are random distributed in a area of 100 x 100 m2

96. Regular grid

97. Baseline for comparing the behavior and performance of DFS algorithms

98. Perturbed grid

100. 6 floor residential building

101. Floor area = 200 m2

102. Floor height = 3 m

103. Femtocells randomly located inside the apartments

104. 1 femtocell per apartment

105. low-medium density scenario

106. 2 apartments per floor

107. high density scenario

109. Outdoor pathloss

110. SIR in the case of regular grid topology with optimal frequency assignment17

112. Break of equilibrium

113. Femtocells simultaneously fall below the threshold

114. SIR distribution could be approximated as a delta function

115. Femtocells at the borders spread the SIR distribution

116. Regular gridrandom network

118. Random topology provide the worst performance

119. High density scenario

121. GDFS outperform ODFS due to the greedy nature of femtocells aiming at maximizing their throughput

122. Random topology (solid line)

124. Regular Gridwith optimal frequency assignment (solid line)

126. FOP set of frequencies assigned to one operator

127. F set of frequencies shared by operators

128. Simulation assumptions:

129. Fixed Outage Level

130. Constant number of femtocells per frequency Franco Mazzenga, Marco Petracca, Remo Pomposini, Francesco Vatalaro, Romeo Giuliano. Performance Evaluation of Spectrum Sharing Algorithms in Single and Multi Operator Scenarios. IEEE VTC2011-Spring International Workshop on Broadband evolved Femtocell Technologies, 15-18 May 2011, Budapest, Hungary.

132. performs an autonomous redistribution of the minimum frequency reuse distance

133. tends to shrink the variance of the obtained distributions

135. Oneeffectivesolutionbased on the adoption of algorithms for cognitive femtocellshasbeenproposed and their performance analyzedthorughsimulation

136. Prosof the proposedsolution:

137. Significantincreaseof the numberofactivenodes in the considered area

138. Verysimpleimplementationof the algorithm due to the usageofelementarystrategiesnotrequiring the coordinationbetweenfemto-BSs

139. Robustness against failure and defections from the algorithm

140. GDFS algorithm allows to reach performance very close to the optimal case

141. Future works:

142. DFSA withcooperationbetweenfemtocells

143. Studyofcomplexfemtocells network topologies and the rulesthatleadstothem22

144. Educationactivities Courses Modulazione Numerica - Prof. Franco Mazzenga - Università Tor Vergata a.a. 2007/2008 Writing a ScientificPaper - UniveritàTor Vergata 14, 15 e 17 Aprile, 2008 Corso inter-dottorato su sistemi embedded, Aprile-giugno 2009, docenti vari, numero ore X Seminars Next Generation Networking: le tecnologie per l'accesso ultrabanda - Villa Mondragone, Università Tor Vergata - 31 Gennaio 2008 – Seminario Le nuove frontiere della qualità nei media digitali - TouradjEbrahimi - Fondazione Ugo Bordoni - 4 Novembre 2008 Nuove frontiere nella gestione dello spettro radio – Joseph Mitola III – Fondazione Ugo Bordoni – 18 Giugno 2009 School Scuola di Dottorato in Ingegneria dell'Informazione - Università di Napoli Federico II 25-29 Febbraio 2008 - 40 ore Lipari Summer School on "Mobile Computing and Communications: Towards the Next Generation of Networks" - 17-24 Luglio 2010 Didattica Cultore della materia “Software per le Telecomunicazioni” OFDM seminar within the course “Sistemi di radiocomunicazioni” 23

146. Cognitive Radio

147. Opportunistic Spectrum Access

148. Dynamic Spectrum Management

149. 3GPP and 4G Femtocellsytems24

151. Andrea Detti, Pierpaolo Loreti, Remo Pomposini, “On the Performance Anomaly in WiMAXnetworks”, Wiley Journal on Wireless Communications and Mobile Computing, SpecialIssue on Wireless Technologies AdvancesforEmergency and RuralCommunications, 2008, ISSN: 1530-8669, doi: 10.1002/wcm.677

152. Book chapter

153. Franco Mazzenga, Marco Petracca, Remo Pomposini, Francesco Vatalaro. ImprovingQoSofFemtocells in Multi-operatorEnvironments. Springer Book on Trustworthy Internet

154. International Conference

155. Franco Mazzenga, Marco Petracca, Remo Pomposini, Francesco Vatalaro, Romeo Giuliano. Performance Evaluation of Spectrum Sharing Algorithms in Single and Multi Operator Scenarios. IEEE VTC2011-Spring International Workshop on Broadband evolved Femtocell Technologies, 15-18 May 2011, Budapest, Hungary.

156. F. Mazzenga, M. Petracca, R. Pomposini, F. Vatalaro, R. Giuliano. AlgorithmsforDynamicFrequencySelectionforFemto-cellsofDifferentOperators. In: 21st IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2010), Istanbul, Turkey, September 26-29 2010

157. F. Mazzenga, M. Petracca, R. Pomposini, F. Vatalaro. Impact on QoSofFemtocellsDefectingfromDynamicFrequencySelectionAlgorithms. In: 21st International Tyrrhenian Workshop on DigitalCommunications (ITWDC 2010): Trustworthy Internet, Ponza, Italy, September 2-8

159. Marco Petracca, Franco Mazzenga, Remo Pomposini, Francesco Vatalaro, Romeo Giuliano. Impact of Control Channel Design on Cooperative Spectrum Sensing in Opportunistic Spectrum Access Networks. First International Conference on Advances in Cognitive Radio (COCORA 2011). 17-22 April 2011, Budapest, Hungary.

160. Marco Petracca, Remo Pomposini, Francesco Vatalaro. Dynamic Spectrum Access Techniques for Preservation of Environment and Cultural Heritage. 20th IEEE International Conference on Collaboration Technologies and Infrastructures. June 27th - 29th, 2011, Paris, France.

161. Andrea Detti, Claudio Loreti, Remo Pomposini, “OverlayBorůvkabasedAd-hocMulticastProtocol – Demonstration”, in ProceedingsofFifthAnnualMediterranean Ad Hoc Networking Workshop (Med-Hoc-Net 2006), Demo Session, Lipari, Sicilia, Italy, 14-17 Giugno 2006

162. Andrea Detti, Remo Pomposini, Roberto Zanetti, “A cross layerversionof OBAMP based on a proactiverouting: description and MANET test-bed”, in Proceedingsof First IEEE conference on Wireless Rural and EmergencyCommunications (WRECOM 2007), Roma, 1-2 Ottobre 2007

163. SubmittedPapers

164. Franco Mazzenga, Marco Petracca, Remo Pomposini, Francesco Vatalaro, Romeo Giuliano. Opportunistic Spectrum Access based on Underlay UWB Signalling. 2011 IEEE International Conference on Ultra-Wideband. 14-15 September 2011, Bologna Italy.26 Publications 2/2

166. network operators make arrangements one with each other to allow the reciprocal exchange of operating frequency channels

167. the simultaneous mutual interchange of spectrum bands among network operators is not currently permitted

168. Policy programmefor the use of the European Union’s radio spectrum foresees an efficient and flexible spectrum management as well as the promotion of collective use of spectrum.

170. GDFS and ODFS show similarperformances

171. Perturbedgrid

172. GDFS slightlyoutperforms the ODFS

173. PC leadsto the best performance

174. Pout= 5%, activefemtocells

175. Random network: 14  68 femtocells

176. Perturbedgrid: 66120 femtocells

177. Increasing fiincrease the number of active femtocells per frequencies

178. Random Network, Pout= 5%

179. 2 freq: 34 served femtocells per frequency

180. 3 freq: 47 active femtocells per frequency

181. Regular grid

183. Femtocells can or can not adopt the DFS algorithm

184. Some femtocells are selfish

185. They do not turn into sensing mode

186. The selfish behaviour of femtocells does not cause a marked decrease of performanceF. Mazzenga, M. Petracca, R. Pomposini, F. Vatalaro. Impact on QoS of Femtocells Defecting from Dynamic Frequency Selection Algorithms. In: 21st International Tyrrhenian Workshop on Digital Communications (ITWDC 2010): Trustworthy Internet, Ponza, Italy, September 2-8