Abstract
Interference alignment (IA) is a novel technique that can effectively eliminate the interference and approach the sum capacity of wireless sensor networks (WSNs) when the signal-to-noise ratio (SNR) is high, by casting the desired signal and interference into different signal subspaces. The traditional alternating minimization interference leakage (AMIL) algorithm for IA shows good performance in high SNR regimes, however, the complexity of the AMIL algorithm increases dramatically as the number of users and antennas increases, posing limits to its applications in the practical systems. In this paper, a novel IA algorithm, called directional quartic optimal (DQO) algorithm, is proposed to minimize the interference leakage with rapid convergence and low complexity. The properties of the AMIL algorithm are investigated, and it is discovered that the difference between the two consecutive iteration results of the AMIL algorithm will approximately point to the convergence solution when the precoding and decoding matrices obtained from the intermediate iterations are sufficiently close to their convergence values. Based on this important property, the proposed DQO algorithm employs the line search procedure so that it can converge to the destination directly. In addition, the optimal step size can be determined analytically by optimizing a quartic function. Numerical results show that the proposed DQO algorithm can suppress the interference leakage more rapidly than the traditional AMIL algorithm, and can achieve the same level of sum rate as that of AMIL algorithm with far less iterations and execution time.
Highlights
Wireless sensor networks (WSNs) have received considerable attention, and have been applied to a large number of scenarios in recent years [1]
We investigate the properties of the alternating minimization interference leakage (AMIL) algorithm, and discover that the difference between the consecutive iteration results of the AMIL algorithm will approximately point to the convergence solution when the precoding and decoding matrices obtained from the intermediate iterations are sufficiently close to their convergence values
It has been found that if the AMIL algorithm can converge to a point where the interference leakage is very small, there exist fixed linear transformations TV and TU that exert on the deviations when the current point is sufficiently close to the convergence value
Summary
Wireless sensor networks (WSNs) have received considerable attention, and have been applied to a large number of scenarios in recent years [1]. With the growth in network scale, interference management has become one of the major challenges in WSNs where multiple users often share some common resources simultaneously and high data rates are often demanded. One recent interesting interference management scheme that can approach the channel capacity is interference alignment (IA), which was firstly studied by Maddah-Ali et al [6] as well as. The degrees of freedom (DoFs), which serve as one key measure of the channel capacity, were studied by Lee et al [9] in the case of the MIMO Y channel and by Cadambe and Jafar [10] in the case of relay networks. Sharma et al [16] have proposed a novel spectral coexistence mechanism which takes advantage of the IA technique
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