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

Interference mitigation using group decoding in multiantenna systems

fi=vertaisarvioitu|en=peerReviewed

Esquemas de pré-codificação IA com IB-DFE para sistemas MC-CDMA

Mestrado em Engenharia Eletrónica e TelecomunicaçõesTo achieve high bit rates, needed to meet the quality of service requirements of future multimedia applications, multi-carrier code division multiple access (MC-CDMA) has been considered as a candidate air-interface. Interference alignment (IA) is a promising technique that allows high capacity gains in interfering channels. On the other hand, iterative block decision feedback equalization (IB-DFE) based receivers can efficiently exploit the inherent space-frequency diversity of the MIMO MC-CDMA systems. In this thesis we proposed an IA precoding at the transmitter with IB-DFE based processing at the receiver for MC-CDMA systems. The IA precoding is applied at chip level instead of the data symbols level, as in the conventional IA based systems. The receiver is designed in two steps: first the equalizers based on zero forcing (ZF) or minimum mean square error (MMSE) are used to remove the aligned users´ interference. Then and after a whitening noise process, an IB-DFE based equalizer is designed to remove both the residual inter-user aligned and inter-carrier interferences. The results have shown that the obtained performance is very close to the one obtained by the optimal matched filter, with few iterations at the receiver side.Para atingir maiores ritmos de transmissão, as futures aplicações multimédia necessitam de atingir a qualidade de serviço necessária. Para isso, o multi-carrier code division multiple access (MC-CDMA) tem sido apontado como um forte candidato para interface ar dos futuros sistemas celulares. O Interference Alignment (IA) ou alinhamento de interferência é uma técnica promissora que permite ter altos ganhos de capacidade em canais com interferência. Por outro lado, temos receptores baseados no conceito iterative block decision feedback equalization(IB-DFE) que conseguem tirar partido, de uma forma eficiente, da inerente diversidade espaço-frequência dos sistemas MIMO MC-CDMA. Nesta dissertação é implementada uma pré-codificação baseada no conceito de IA considerando três transmissores (ou estações base) juntamente, com um processamento IB-DFE no receptor para sistemas MC-CDMA.A pré-codificação é aplicada ao nível de chip em vez de ser aplicado ao nível dos dados. O receptor é projectado em dois passos: em primeiro lugar equalizadores baseados em ZF ou em MMSE são utilizados para remover a interferência alinhada dos restantes utilizadores. De seguida, e após aplicar um processo de branqueamento do ruído ao sinal à saída do primeiro equalizador, um segundo equalizador baseado em IB-DFE é projectado para remover a interferência inter-utilizador residual e também a interferência residual entre portadoras. Os resultados obtidos mostraram-se satisfatórios na remoção da interferência obtendo-se um desempenho muito próximo do obtido considerando um filtro adaptado

Sparse Signal Processing Concepts for Efficient 5G System Design

As it becomes increasingly apparent that 4G will not be able to meet the emerging demands of future mobile communication systems, the question what could make up a 5G system, what are the crucial challenges and what are the key drivers is part of intensive, ongoing discussions. Partly due to the advent of compressive sensing, methods that can optimally exploit sparsity in signals have received tremendous attention in recent years. In this paper we will describe a variety of scenarios in which signal sparsity arises naturally in 5G wireless systems. Signal sparsity and the associated rich collection of tools and algorithms will thus be a viable source for innovation in 5G wireless system design. We will discribe applications of this sparse signal processing paradigm in MIMO random access, cloud radio access networks, compressive channel-source network coding, and embedded security. We will also emphasize important open problem that may arise in 5G system design, for which sparsity will potentially play a key role in their solution.Comment: 18 pages, 5 figures, accepted for publication in IEEE Acces

On Enabling Concurrent Communications in Wireless Networks

Today innumerable devices use the wireless spectrum for communication, including cell-phones, WiFi devices, military radios, public safety radios, satellite phones etc. This crowding is limiting the experience of each device either through interference or by waiting fortheir turn to communicate. So, how do we allow a limited spectral resource to reliably scale to many more devices? This is possible through concurrent communication where multiple links share the spectrum and communicate simultaneously using multi-antenna techniques. One promising technique is Interference Alignment (IA), that has been shown to be Degrees-of-Freedom optimal under some conditions. Still, IA requires accurate channel knowledge to be effective and its ability to achieve high throughput under time varying wireless conditions is yet unproven. We make progress towards understanding these limitations and provide viable solutions.We study an IA system under different models of the time varying channel and derive expressions for the achieved rate over time and the system throughput. Using these, we can arrive at the optimal duration of the data phase that maximizes throughput. We proposetwo strategies that help to counter the effects of a time varying channel. First, data aided receiver beam-tracking along with link adaptation provides a sizable improvement in the received signal to interference and noise ratio. Second, updating the transmit beams during data transmission using short feedback pilots improves alignment at the receivers. In faster varying channels, we get a more stable achieved rate whereas in slower varying channels, we see additional throughput gains. The conclusion from this work is that an IA system must be trained more frequently than the channel coherence time to ensure high throughput and beam adaptation during the data phase gives significant robustness to the system.Lastly, we present an IA based medium access control (MAC) protocol that outperforms traditional protocols. Our concurrent carrier sense multiple access (CSMA) protocol based on beam-nulling is compatible with CSMA and increases the sum throughput by 2 to 3x.We also show that IA outperforms optimal time division multiple access under time varying conditions. Hence a well-designed IA system can enable reliable concurrent communications in a wireless network