314 research outputs found
State of the Art, Taxonomy, and Open Issues on Cognitive Radio Networks with NOMA
The explosive growth of mobile devices and the rapid increase of wideband
wireless services call for advanced communication techniques that can achieve
high spectral efficiency and meet the massive connectivity requirement.
Cognitive radio (CR) and non-orthogonal multiple access (NOMA) are envisioned
to be important solutions for the fifth generation wireless networks.
Integrating NOMA techniques into CR networks (CRNs) has the tremendous
potential to improve spectral efficiency and increase the system capacity.
However, there are many technical challenges due to the severe interference
caused by using NOMA. Many efforts have been made to facilitate the application
of NOMA into CRNs and to investigate the performance of CRNs with NOMA. This
article aims to survey the latest research results along this direction. A
taxonomy is devised to categorize the literature based on operation paradigms,
enabling techniques, design objectives and optimization characteristics.
Moreover, the key challenges are outlined to provide guidelines for the domain
researchers and designers to realize CRNs with NOMA. Finally, the open issues
are discussed.Comment: This paper has been accepted by IEEE Wireless Communications
Magazine. Pages 16, Figures
Spectral Efficiency of Multi-User Adaptive Cognitive Radio Networks
In this correspondence, the comprehensive problem of joint power, rate, and
subcarrier allocation have been investigated for enhancing the spectral
efficiency of multi-user orthogonal frequency-division multiple access (OFDMA)
cognitive radio (CR) networks subject to satisfying total average transmission
power and aggregate interference constraints. We propose novel optimal radio
resource allocation (RRA) algorithms under different scenarios with
deterministic and probabilistic interference violation limits based on a
perfect and imperfect availability of cross-link channel state information
(CSI). In particular, we propose a probabilistic approach to mitigate the total
imposed interference on the primary service under imperfect cross-link CSI. A
closed-form mathematical formulation of the cumulative density function (cdf)
for the received signal-to-interference-plus-noise ratio (SINR) is formulated
to evaluate the resultant average spectral efficiency (ASE). Dual decomposition
is utilized to obtain sub-optimal solutions for the non-convex optimization
problems. Through simulation results, we investigate the achievable performance
and the impact of parameters uncertainty on the overall system performance.
Furthermore, we present that the developed RRA algorithms can considerably
improve the cognitive performance whilst abide the imposed power constraints.
In particular, the performance under imperfect cross-link CSI knowledge for the
proposed `probabilistic case' is compared to the conventional scenarios to show
the potential gain in employing this scheme
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