Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/522334
Title: Joint Subchannel Assignment and Power Allocation for OFDMA Femtocell Networks
Authors: Sch. of Electr. Eng. & Comput. Sci., Univ. of Newcastle, Newcastle, NSW, Australia;Duy Trong Ngo ; Khakurel, Suman ; Tho Le-Ngoc
subject: OFDM modulation; approximation theory; convex programming; femtocellular radio; geometric programming; AGM approximation-based solution; DC approximation-based solutions; FUE; OFDM subchannels; OFDMA femtocell networks; SCA-based power optimization solutions; SINR; arithmetic-geometric mean approximation based solution; base stations; convex relaxation programs; femtocell user equipments; geometric programming; iterative approach; joint subchannel and power allocation algorithm; network capacity; nonconvex power allocation problem; orthogonal frequency-division multiple access mixed femtocell-macrocell network deployment; signal-to-interference-plus-noise ratio; subchannel assignment; successive convex approximation approach; Approximation methods; Interference; Joints; Macrocell networks; OFDM; Resource management; Signal to noise ratio; Convex optimization; femtocell; heterogeneous networks; iterative algorithm; macrocell QoS protection; power allocation; subchannel assignment; successive convex approximation;
Year: 2014
Publisher: IEEE
Abstract: In this paper, we propose a joint subchannel and power allocation algorithm for the downlink of an orthogonal frequency-division multiple access (OFDMA) mixed femtocell/macrocell network deployment. Specifically, the total throughput of all femtocell user equipments (FUEs) is maximized while the network capacity of an existing macrocell is always protected. Towards this end, we employ an iterative approach in which OFDM subchannels and transmit powers of base stations (BS) are alternatively assigned and optimized at every step. For a fixed power allocation, we prove that the optimal policy in each cell is to give each subchannel to the user with the highest signal-to-interference-plus-noise ratio (SINR) on that subchannel. For a given subchannel assignment, we adopt the successive convex approximation (SCA) approach and transform the highly nonconvex power allocation problem into a sequence of convex subproblems. In the arithmetic-geometric mean (AGM) approximation, we apply geometric programming to find optimal solutions after condensing a posynomial into a monomial. On the other hand, logarithmic and underline{d}ifference-of-two-underline{c}oncave-functions (D.C.) approximations lead us to solving a series of convex relaxation programs. With the three proposed SCA-based power optimization solutions, we show that the overall joint subchannel and power allocation algorithm converges to some local maximum of the original design problem. While a central processing unit is required to implement the AGM approximation-based solution, each BS locally computes the optimal subchannel and power allocation for its own servicing cell in the logarithmic and D.C. approximation-based solutions. Numerical examples confirm the merits of the proposed algorithm.
URI: http://localhost/handle/Hannan/280935
http://localhost/handle/Hannan/522334
ISSN: 1536-1276
volume: 13
issue: 1
Appears in Collections:2014

Files in This Item:
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6678362.pdf859.78 kBAdobe PDF
Title: Joint Subchannel Assignment and Power Allocation for OFDMA Femtocell Networks
Authors: Sch. of Electr. Eng. & Comput. Sci., Univ. of Newcastle, Newcastle, NSW, Australia;Duy Trong Ngo ; Khakurel, Suman ; Tho Le-Ngoc
subject: OFDM modulation; approximation theory; convex programming; femtocellular radio; geometric programming; AGM approximation-based solution; DC approximation-based solutions; FUE; OFDM subchannels; OFDMA femtocell networks; SCA-based power optimization solutions; SINR; arithmetic-geometric mean approximation based solution; base stations; convex relaxation programs; femtocell user equipments; geometric programming; iterative approach; joint subchannel and power allocation algorithm; network capacity; nonconvex power allocation problem; orthogonal frequency-division multiple access mixed femtocell-macrocell network deployment; signal-to-interference-plus-noise ratio; subchannel assignment; successive convex approximation approach; Approximation methods; Interference; Joints; Macrocell networks; OFDM; Resource management; Signal to noise ratio; Convex optimization; femtocell; heterogeneous networks; iterative algorithm; macrocell QoS protection; power allocation; subchannel assignment; successive convex approximation;
Year: 2014
Publisher: IEEE
Abstract: In this paper, we propose a joint subchannel and power allocation algorithm for the downlink of an orthogonal frequency-division multiple access (OFDMA) mixed femtocell/macrocell network deployment. Specifically, the total throughput of all femtocell user equipments (FUEs) is maximized while the network capacity of an existing macrocell is always protected. Towards this end, we employ an iterative approach in which OFDM subchannels and transmit powers of base stations (BS) are alternatively assigned and optimized at every step. For a fixed power allocation, we prove that the optimal policy in each cell is to give each subchannel to the user with the highest signal-to-interference-plus-noise ratio (SINR) on that subchannel. For a given subchannel assignment, we adopt the successive convex approximation (SCA) approach and transform the highly nonconvex power allocation problem into a sequence of convex subproblems. In the arithmetic-geometric mean (AGM) approximation, we apply geometric programming to find optimal solutions after condensing a posynomial into a monomial. On the other hand, logarithmic and underline{d}ifference-of-two-underline{c}oncave-functions (D.C.) approximations lead us to solving a series of convex relaxation programs. With the three proposed SCA-based power optimization solutions, we show that the overall joint subchannel and power allocation algorithm converges to some local maximum of the original design problem. While a central processing unit is required to implement the AGM approximation-based solution, each BS locally computes the optimal subchannel and power allocation for its own servicing cell in the logarithmic and D.C. approximation-based solutions. Numerical examples confirm the merits of the proposed algorithm.
URI: http://localhost/handle/Hannan/280935
http://localhost/handle/Hannan/522334
ISSN: 1536-1276
volume: 13
issue: 1
Appears in Collections:2014

Files in This Item:
File SizeFormat 
6678362.pdf859.78 kBAdobe PDF
Title: Joint Subchannel Assignment and Power Allocation for OFDMA Femtocell Networks
Authors: Sch. of Electr. Eng. & Comput. Sci., Univ. of Newcastle, Newcastle, NSW, Australia;Duy Trong Ngo ; Khakurel, Suman ; Tho Le-Ngoc
subject: OFDM modulation; approximation theory; convex programming; femtocellular radio; geometric programming; AGM approximation-based solution; DC approximation-based solutions; FUE; OFDM subchannels; OFDMA femtocell networks; SCA-based power optimization solutions; SINR; arithmetic-geometric mean approximation based solution; base stations; convex relaxation programs; femtocell user equipments; geometric programming; iterative approach; joint subchannel and power allocation algorithm; network capacity; nonconvex power allocation problem; orthogonal frequency-division multiple access mixed femtocell-macrocell network deployment; signal-to-interference-plus-noise ratio; subchannel assignment; successive convex approximation approach; Approximation methods; Interference; Joints; Macrocell networks; OFDM; Resource management; Signal to noise ratio; Convex optimization; femtocell; heterogeneous networks; iterative algorithm; macrocell QoS protection; power allocation; subchannel assignment; successive convex approximation;
Year: 2014
Publisher: IEEE
Abstract: In this paper, we propose a joint subchannel and power allocation algorithm for the downlink of an orthogonal frequency-division multiple access (OFDMA) mixed femtocell/macrocell network deployment. Specifically, the total throughput of all femtocell user equipments (FUEs) is maximized while the network capacity of an existing macrocell is always protected. Towards this end, we employ an iterative approach in which OFDM subchannels and transmit powers of base stations (BS) are alternatively assigned and optimized at every step. For a fixed power allocation, we prove that the optimal policy in each cell is to give each subchannel to the user with the highest signal-to-interference-plus-noise ratio (SINR) on that subchannel. For a given subchannel assignment, we adopt the successive convex approximation (SCA) approach and transform the highly nonconvex power allocation problem into a sequence of convex subproblems. In the arithmetic-geometric mean (AGM) approximation, we apply geometric programming to find optimal solutions after condensing a posynomial into a monomial. On the other hand, logarithmic and underline{d}ifference-of-two-underline{c}oncave-functions (D.C.) approximations lead us to solving a series of convex relaxation programs. With the three proposed SCA-based power optimization solutions, we show that the overall joint subchannel and power allocation algorithm converges to some local maximum of the original design problem. While a central processing unit is required to implement the AGM approximation-based solution, each BS locally computes the optimal subchannel and power allocation for its own servicing cell in the logarithmic and D.C. approximation-based solutions. Numerical examples confirm the merits of the proposed algorithm.
URI: http://localhost/handle/Hannan/280935
http://localhost/handle/Hannan/522334
ISSN: 1536-1276
volume: 13
issue: 1
Appears in Collections:2014

Files in This Item:
File SizeFormat 
6678362.pdf859.78 kBAdobe PDF