Interference Alignment in Multi-Input Multi-Output Cognitive Radio-Based Network

This study investigates the interference alignment techniques for cognitive radio networks toward 5G to meet the demand and challenges for future wireless communications requirements. In this context, we examine the performance of the interference alignment in two parts. In the first part of this chapter, a multi-input multi-output (MIMO) cognitive radio network in the presence of multiple secondary users (SUs) is investigated. The proposed model assumes that linear interference alignment is used at the primary system to lessen the interference between primary and secondary networks. Herein, we derive the closed-form mathematical equations for the outage probability considering the interference leakage occurred in the primary system. The second part of this study analyzes the performance of interference alignment for underlay cognitive two-way relay networks with channel state information (CSI) quantization error. Here, a two-way amplify-and-forward relaying scheme is considered for independent and identically distributed Rayleigh fading channel. The closed-form average pairwise error probability expressions are derived, and the effect of CSI quantization error is analyzed based on the bit error rate performance. Finally, we evaluate the instantaneous capacity for both primary and secondary networks*

A Distributed Approach to Interference Alignment in OFDM-based Two-tiered Networks

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.Comment: 15 pages, 10 figures, accepted and to appear in IEEE Transactions on Vehicular Technology Special Section: Self-Organizing Radio Networks, 2013. Authors' final version. Copyright transferred to IEE

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

Channels Reallocation In Cognitive Radio Networks Based On DNA Sequence Alignment

Nowadays, It has been shown that spectrum scarcity increased due to tremendous growth of new players in wireless base system by the evolution of the radio communication. Resent survey found that there are many areas of the radio spectrum that are occupied by authorized user/primary user (PU), which are not fully utilized. Cognitive radios (CR) prove to next generation wireless communication system that proposed as a way to reuse this under-utilised spectrum in an opportunistic and non-interfering basis. A CR is a self-directed entity in a wireless communications environment that senses its environment, tracks changes, and reacts upon its findings and frequently exchanges information with the networks for secondary user (SU). However, CR facing collision problem with tracks changes i.e. reallocating of other empty channels for SU while PU arrives. In this paper, channels reallocation technique based on DNA sequence alignment algorithm for CR networks has been proposed.Comment: 12 page

Space Alignment Based on Regularized Inversion Precoding in Cognitive Transmission

For a two-tier Multiple-Input Multiple-Output (MIMO) cognitive network with common receiver, the precoding matrix has a compact relationship with the capacity performance in the unlicensed secondary system. To increase the capacity of secondary system, an improved precoder based on the idea of regularized inversion for secondary transmitter is proposed. An iterative space alignment algorithm is also presented to ensure the Quality of Service (QoS) for primary system. The simulations reveal that, on the premise of achieving QoS for primary system, our proposed algorithm can get larger capacity in secondary system at low Signal-to-Noise Ratio (SNR), which proves the effectiveness of the algorithm

Vandermonde-subspace Frequency Division Multiplexing for Two-Tiered Cognitive Radio Networks

Vandermonde-subspace frequency division multiplexing (VFDM) is an overlay spectrum sharing technique for cognitive radio. VFDM makes use of a precoder based on a Vandermonde structure to transmit information over a secondary system, while keeping an orthogonal frequency division multiplexing (OFDM)-based primary system interference-free. To do so, VFDM exploits frequency selectivity and the use of cyclic prefixes by the primary system. Herein, a global view of VFDM is presented, including also practical aspects such as linear receivers and the impact of channel estimation. We show that VFDM provides a spectral efficiency increase of up to 1 bps/Hz over cognitive radio systems based on unused band detection. We also present some key design parameters for its future implementation and a feasible channel estimation protocol. Finally we show that, even when some of the theoretical assumptions are relaxed, VFDM provides non-negligible rates while protecting the primary system.Comment: 9 pages, accepted for publication in IEEE Transactions on Communication