Session 2a, 10th June 2008 ICT-MobileSummit 2008 Copyright E 3 project, UPC A Primary Spectrum Management Solution Facilitating Secondary Usage Exploitation Jad Nasreddine, Jordi Pérez-Romero, Oriol Sallent, Ramon Agustí Universitat Politècnica de Catalunya (UPC) Spain

Session 2a, 10th June 2008 ICT-MobileSummit 2008 Copyright E 3 project, UPC Motivation: Spectrum Allocation Actual spectrum allocation is space and time invariant Traffic distribution is non- homogenous in time and space A large amount of the spectrum is underutilized Several licensed bands are saturated A large amount of the spectrum is underutilized Several licensed bands are saturated Decrease in the offered QoS to users  Decrease of operators profits Increase in a RAT traffic  Network infrastructure extensions and cost Decrease in the offered QoS to users  Decrease of operators profits Increase in a RAT traffic  Network infrastructure extensions and cost * FCC, Spectrum Policy Task Force “Report of the Spectrum Efficiency Working Group,” November 15, Spectrum access and not spectrum scarcity reduces spectrum efficiency*

Session 2a, 10th June 2008 ICT-MobileSummit 2008 Copyright E 3 project, UPC Objectives of the Proposed Approach Main objective –Find the best spectrum allocation in a primary network that allows the release of some blocks of spectrum in large geographic zones while guaranteeing the QoS levels of primary users –Spare frequencies could be exchanged between different RATs or operators without a risk of high interference Illustrative Example: WCDMA Networks –Use novel inter-cell interaction indicator (coupling matrices) to prevent the allocation of the same frequency to cells with high interactions –Estimate the number of carriers needed by a WCDMA system –Estimate the number of carriers needed by each cell –Smartly distribute the available carriers among cells in order to increase system performance

Session 2a, 10th June 2008 ICT-MobileSummit 2008 Copyright E 3 project, UPC Main Idea Coupling Matrix –Smart radio indicator that is able to reflect both macroscopic and microscopic properties of the radio network Use coupling matrix properties to develop ASM –Detect relevant changes in the radio interface –Find the best spectrum allocation f 1, f 2, f 3 f1f1 Traffic distribution variation ASM Detection of Traffic distribution variation Find a better allocation f 1, f 2 f3 is released

Session 2a, 10th June 2008 ICT-MobileSummit 2008 Copyright E 3 project, UPC Illustrative Example The same capacity and QoS Some carriers could be released for other RATs/operators or secondary market Use ASM methodology With frequency reuse 1 All carriers are used

Session 2a, 10th June 2008 ICT-MobileSummit 2008 Copyright E 3 project, UPC Spectral Efficiency Approaches Uniform Allocation Same system Allocation 1 The index of spectral efficiency should detect the difference between these two allocations First index: traditional spectrum efficiency in bps/Hz/cell Second index: depends on secondary application and traffic Allocation 2 The index of spectral efficiency should detect that the above allocation is the best allocation

Session 2a, 10th June 2008 ICT-MobileSummit 2008 Copyright E 3 project, UPC Useful Released Surface (URS) For a given frequency allocation: –W (f) : the bandwidth of carrier f, –C (f) : the set of non-contiguous areas where f could be used by another network, – : the surface of area c where f could be used by another network, – : the weight given to area c depending on the expected number of other network’ users in this area

Session 2a, 10th June 2008 ICT-MobileSummit 2008 Copyright E 3 project, UPC ASM Algorithm Measurements Analyze Inter-cell interaction Relevant interaction variation Yes No Allocation Algorithm Λ a is empty Carrier obtained Yes No Ask for more carriers Apply the new allocation to the network Yes No New allocation is better than old allocation u(Λ a )> u(Λ o ) No Yes u(Λ o ) Λ a : new allocation Λ o : old allocation Number of carriers←F Objective←u Constraints ←  Coupling Matrix Properties Simulated Annealing-based

Session 2a, 10th June 2008 ICT-MobileSummit 2008 Copyright E 3 project, UPC Both ASM lead to high SE Results (1/2) Outage Probability threshold 0.05 System with 3 carriers Compare algorithms: –Uniform algorithm –ASM optimizing SE: SA-SE –ASM optimizing URS: SA-URS SA-URS gives the highest URS especially for high traffic load Outage probability constraint is satisfied

Session 2a, 10th June 2008 ICT-MobileSummit 2008 Copyright E 3 project, UPC Results (2/2) SA-SE SA-URS Released areas (in white) for a traffic of 4400 mobiles (the third carrier is fully utilized) Carrier f1Carrier f2

Session 2a, 10th June 2008 ICT-MobileSummit 2008 Copyright E 3 project, UPC Conclusions Introduction of a new ASM methodology with objectives: –An efficient spectrum utilisation of licensed spectrum bands In accordance with the existing load levels –Releasing some carriers for a secondary usage in large geographical areas When the load levels are low enough –Based on a simulated annealing –Maximises a new metric accounting for the geographical area in which each carrier is released. The results show that both metrics are necessary –The two ASM methodologies increase the efficiency by more than double when compared to the uniform distribution –SA-URS gives significantly high results compared to the two other methods Future work –Detailed study of the protection zones to be left in accordance with primary and secondary user characteristics –Dynamic Spectrum allocation in a heterogeneous network: WCDMA and OFDMA systems