A Distributed Approach to Interference Alignment in OFDM-Based Two-Tiered Networks

Abstract

In this contribution, we consider a two-tiered network and focus on the coexistence between the two tiers at physical layer. We target our efforts on a long term evolution advanced (LTE-A) orthogonal frequency division multiple access (OFDMA) macro-cell sharing the spectrum with a randomly deployed second tier of small-cells. In such networks, high levels of co-channel interference between the macro and small base stations (MBS/SBS) may largely limit the potential spectral efficiency gains provided by the frequency reuse 1. To address this issue, we propose a novel cognitive interference alignment based scheme to protect the macro-cell from the cross-tier interference, while mitigating the co-tier interference in the second tier. Remarkably, only local channel state information (CSI) and autonomous operations are required in the second tier, resulting in a completely self-organizing approach for the SBSs. The optimal precoder that maximizes the spectral efficiency of the link between each SBS and its served user equipment is found by means of a distributed one-shot strategy. Numerical findings reveal non-negligible spectral efficiency enhancements with respect to traditional time division multiple access approaches at any signal to noise (SNR) regime. Additionally, the proposed technique exhibits significant robustness to channel estimation errors, achieving remarkable results for the imperfect CSI case and yielding consistent performance enhancements to the network.

Physical-Layer Transmission Cooperative Strategies for Heterogeneous Networks

“…One of the recent and effective approaches to deal with interference issues in heterogeneous networks is the interference alignment (IA) technique [14]. The concept of IA has emerged as an essential approach to align an arbitrary large number of interferers and achieve the maximum degree of freedom (DoF) in interference channels [15,16]. The problem of limited inter-system information exchange in heterogeneous-based systems using IA has been addressed in some publications [17,18].…”

Macro-pico amplitude-space sharing with layered interference alignment

“…Conventional methods to mitigate inter-cell interference mainly involve various orthogonalization-based processing. For example, almost blank subframe (ABS) is a time orthogonal interference coordination scheme; fractional frequency reuse (FFR) is a frequency orthogonal interference coordination scheme; coordinated beamforming (CB) is a spatial orthogonal interference coordination scheme [4][5][6][7]. The vector-space interference alignment (IA) scheme is an advanced orthogonalizationbased interference coordination scheme, where multiple interference are aligned in a subspace while leave the orthogonal signal subspace interference-free [8,9].…”

Improving Macrocell-Small Cell Coexistence Through Adaptive Interference Draining

“…In order to achieve that, IA techniques only use half of the available transmission opportunities, therefore, the opportunistic exploitation of the IA spatial degrees has been recently extended to incorporate the frequency dimension. By doing so, one can improve the transmission rates of the small cells by exploring new transmission opportunities (i.e., degrees of freedom) in both the frequency and space domains [21][22][23][24][25][26]. It thus becomes possible for the small cells to enable interferencefree communications by leveraging the spatial and frequency precoding.…”

“…It thus becomes possible for the small cells to enable interferencefree communications by leveraging the spatial and frequency precoding. Moreover, the opportunistic IA solution can be combined with other interference management techniques, such as successive interference cancellation [26], [27] or zero forcing equalization [28]. In order to perform opportunistic IA, the complete knowledge of the full channel state information (CSI) is required and the transmitters are required to cooperate for the joint design of the precoding matrices.…”

“…In order to perform opportunistic IA, the complete knowledge of the full channel state information (CSI) is required and the transmitters are required to cooperate for the joint design of the precoding matrices. However, IA techniques are limited by the fact that IA solutions only exist for certain problem dimensions, which are given by the size of the antenna set and the number of the interfering signals to be aligned [20], [23], [26], [29]. Hence, in practice, every new transmitter imposes additional constraints and an IA scheme can only suppress a limited number of interfering signals, since the number of antennas (especially at the receiver side) is limited.…”