Interference Management in Heterogeneous Networks with Blind Transmitters

Future multi-tier communication networks will require enhanced network capacity and reduced overhead. In the absence of Channel State Information (CSI) at the transmitters, Blind Interference Alignment (BIA) and Topological Interference Management (TIM) can achieve optimal Degrees of Freedom (DoF), minimising network's overhead. In addition, Non-Orthogonal Multiple Access (NOMA) can increase the sum rate of the network, compared to orthogonal radio access techniques currently adopted by 4G networks. Our contribution is two interference management schemes, BIA and a hybrid TIM-NOMA scheme, employed in heterogeneous networks by applying user-pairing and Kronecker Product representation. BIA manages inter- and intra-cell interference by antenna selection and appropriate message scheduling. The hybrid scheme manages intra-cell interference based on NOMA and inter-cell interference based on TIM. We show that both schemes achieve at least double the rate of TDMA. The hybrid scheme always outperforms TDMA and BIA in terms of Degrees of Freedom (DoF). Comparing the two proposed schemes, BIA achieves more DoF than TDMA under certain restrictions, and provides better Bit-Error-Rate (BER) and sum rate performance to macrocell users, whereas the hybrid scheme improves the performance of femtocell users.Comment: 30 pages, 18 figure

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe

The Practical Challenges of Interference Alignment

Interference alignment (IA) is a revolutionary wireless transmission strategy that reduces the impact of interference. The idea of interference alignment is to coordinate multiple transmitters so that their mutual interference aligns at the receivers, facilitating simple interference cancellation techniques. Since IA's inception, researchers have investigated its performance and proposed improvements, verifying IA's ability to achieve the maximum degrees of freedom (an approximation of sum capacity) in a variety of settings, developing algorithms for determining alignment solutions, and generalizing transmission strategies that relax the need for perfect alignment but yield better performance. This article provides an overview of the concept of interference alignment as well as an assessment of practical issues including performance in realistic propagation environments, the role of channel state information at the transmitter, and the practicality of interference alignment in large networks.Comment: submitted to IEEE Wireless Communications Magazin