Joint Subchannel Assignment and Power Allocation for OFDMA Femtocell Networks

被引:211
|
作者
Duy Trong Ngo [1 ]
Khakurel, Suman [2 ]
Tho Le-Ngoc [2 ]
机构
[1] Univ Newcastle, Sch Elect Engn & Comp Sci, Callaghan, NSW 2308, Australia
[2] McGill Univ, Dept Elect & Comp Engn, Montreal, PQ H3A 0E9, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Convex optimization; femtocell; heterogeneous networks; iterative algorithm; power allocation; macrocell QoS protection; subchannel assignment; successive convex approximation; INTERFERENCE MANAGEMENT; OPTIMIZATION;
D O I
10.1109/TWC.2013.111313.130645
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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 difference-of-two-concave-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.
引用
收藏
页码:342 / 355
页数:14
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