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This thesis presentation explores the performance evaluation of an adaptive sub-carrier allocation scheme for OFDMA in wireless communications. The presentation includes an overview of OFDM, OFDM-based multiple access schemes, and the adaptive sub-carrier allocation algorithm. Simulation results and conclusions are also discussed.
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HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Performance evaluation of adaptive sub-carrier allocation scheme for OFDMA Thesis presentation 16th Jan 2007 Author: Li Xiao Supervisor: Professor Riku Jäntti Instructor: Lic.Sc Boris Makarevitch Place: Communications Laboratory
Introduction Overview of OFDM OFDM based multiple access schemes Adaptive sub-carrier allocation algorithm Simulation Conclusions HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Agenda
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Introduction Background • Multi-carrier transmission methods attract much focus to support high speed and reliable wireless communications • A good OFDMA sub-carrier allocation scheme should use spectral as efficiently as possible and achieve minimum cost of service based upon user’s QoS requirement Objectives • Transmission power minimization as cost of service in Downlink and Uplink • Performance evaluation of adaptive sub-carrier allocation for OFDMA Methodology • Adaptive OFDMA sub-carrier allocation algorithm implementation in Matlab • Performance comparison among adaptive OFDMA sub-carrier allocation scheme and other static schemes
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory OFDM • Dividing the total bandwidth into a number of sub-carriers • OFDM realization • Intersymbol interference • Intercarrier interference • Cyclic prefix
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory OFDM Based Multiple Access Schemes
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory OFDMA • Each user transmits on a certain number of OFDM sub-carriers during all time slots • Static sub-carriers assignment and dynamic sub-carriers assignment • Multirate system • Multiuser diversity • Adaptive modulation (bit rate, transmission power, channel coding rate or scheme)
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Mobile WiMAX • Extension of WiMAX for fixed access • Scalable OFDMA • High data rate • Quality of Service • Scalability • Security • Mobility
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Adaptive sub-carrier allocation algorithm Adaptive means • Number of sub-carriers each user needs is adaptive • Sub-carriers allocation among users is adaptive • Bit loading to sub-carriers is adaptive • Adaptive modulation scheme for each sub-carrier Users’ QoS requirement • Minimum Reserved Rate • Bit Error Rate
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Downlink system structure of OFDMA • BS has the perfect knowledge of instantaneous channel information for all users • Bandwidth of each sub-carrier is smaller than channel coherence bandwidth • Each sub-carrier can only be occupied by one user • No free sub-carrier left
Objective function Transmission power minimization Downlink: Minimize the interference from BS in question to the MSs in other cells Uplink: MS battery saving Constraints Bit rate (bit/symbol) BER requirement Three sub-algorithms Number of sub-carriers determination Sub-carriers allocation Bit loading HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Adaptive sub-carrier allocation algorithm
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Number of sub-carriers determination • Inputs: Each user’s bit rate constraint and average channel gain for each user • Output: Number of sub-carriers each user gets assigned • Two types of sub-carriers: Minimum required sub-carrier and Extra sub-carrier • Minimum required sub-carriers are to fulfill the user’s bit rate constraint in the case that maximum amount of bits will be transmitted in each sub-carrier • Extra sub-carriers will share bits with minimum required sub-carriers so that the loaded bits in each sub-carrier can be reduced and with an adaptive modulation scheme transmission power to all user can decrease • No free sub-carrier left
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Sub-carrier allocation • Inputs: Channel State Information for each user and number of sub-carriers each user gets assigned • Output: sub-carriers allocation Phase 1: Constructive initial allocation • List the sub-carriers for each user in descend order according to channel gain • Check sub-carriers user by user if the number of sub-carrier each user gets is achieved or the sub-carrier has already been assigned to some users • If both are NO, assign the sub-carrier to this user, otherwise skip this user to next user
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Sub-carrier allocation Phase 1 may achieve only a local minimum but not total minimum transmission power Phase 2: Iterative improvement • For every iteration, swap a pair of sub-carriers allocated to two users such that the result power can be reduced further • Power reduction factor is the cost function in order to select the pair of users and pair of sub-carriers which can reduce power most • Iteration is over when the maximum possible power reduction is less than zero
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Bit loading • Inputs: Sub-carriers allocation, channel gain and bit rate constraint • Output: Bits loaded to achieve each user’s bit rate constraint Levin-Campello algorithm • Each time selecting the sub-carrier that requires the least additional power to add one more bit • Check if the maximum amount of bits loaded in this sub-carrier has already been achieved and if this user’s bit rate constraint has been fulfilled • If both are NO, loading one more bit to this sub-carrier, otherwise selecting the sub-carrier which requires second least additional power and repeat 2
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Simulation
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Simulation results:Number of sub-carriers determination
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Simulation results:Sub-carriers allocation
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Simulation results:Bit loading
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Simulation results:BER performance • Minimum 11.33dB gain in SNR using Adaptive allocation OFDM without extra sub-carriers over OFDM Interleave-FDMA • 11.84dB gain over OFDM-TDMA • 14.35dB gain over OFDM-FDMA • 6.91dB gain from extra sub-carrier presence compared with no extra sub-carrier case
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Simulation results:Convergence of algorithm
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Conclusions • Adaptive sub-carriers allocation algorithm can enhance the BER performance compared with static schemes • The use of extra sub-carriers can improve the BER performance and decrease the total transmission power further • Speed of the algorithm (convergence speed) is fast to meet the real time application requirements • The speed of algorithm is not affected by the number of users much which guaranttes it perform well in high load system • BS could use algorithm to increase the total number of users that can be accommodated for a given power budget
HELSINKI UNIVERSITY OF TECHNOLOGY Communications Laboratory Future study • Minimization of transmission power in Uplink • Scalable OFDMA Thank you!