Achievable Rate of Spectrum Sharing Cognitive Radio Multiple-Antenna Channels

Sboui, Lokman; Ghazzai, Hakim; Rezki, Zouheir; Alouini, Mohamed‐Slim

doi:10.1109/twc.2015.2427281

Cited by 24 publications

(19 citation statements)

References 29 publications

(36 reference statements)

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“…Applications [56][57][58][59][60] Cognitive Radio Networks [30,41,47,61] K User Interference Channel [27,30,31,46,47] K User M × N MIMO Interference Channels [62,63] 5G Cellular Wireless Networks [64][65][66] Cooperative Interference Networks [66,67] Multihop Interference Networks [68,69] Ad hoc Networks [70,71] Physical Layer Security [72,73] Satellite Networks [74,75] D2D Networks [50,76] IoT Networks [34,35,38,51] Heterogeneous Networks…”

Section: Referencesmentioning

confidence: 99%

“…Similarly, the work in ref. [68] investigates both orthogonal and non-orthogonal transmission of the SU, with the aim of determining spectral efficiency gain of an uplink MIMO CR system. In this work, the SU is allowed to share the spectrum with the PU by using a unique space alignment technique along with an interference temperature threshold technique to ensure a non-zero SU rate.…”

Section: Single User Mimo Su Linkmentioning

confidence: 99%

See 1 more Smart Citation

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

Abdulkadir

Simpson

Sun

2019

JSAN

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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.

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Section: Referencesmentioning

confidence: 99%

Section: Single User Mimo Su Linkmentioning

confidence: 99%

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

Abdulkadir

Simpson

Sun

2019

JSAN

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“…In this subsection, we provide a bisection method to find the optimal value of γ when just imperfect interferers' CSI are known. By applying (47), the optimization problem (38) is turned to a feasibility check problem of finding w with the constraints (47) for a given value of γ.…”

Section: B Optimal Sinr Solutionmentioning

confidence: 99%

Optimal Relaying Beamforming in Multiple Access Broadcast Channel (MABC) Bidirectional Cognitive Radio Networks in Presence of Interferers

Zaeri-Amirani

Afghah

Ashdown

2018

Int J Wireless Inf Networks

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In this paper, a general cognitive radio system consisting of a set of users with different level of spectrum access including two primary transceivers and several types of secondary users is considered.It is assumed that two secondary users operate based on an underlay model at the same frequency bandwidth and at the same time as the primary users based on a multiple access broadcast channel (MABC) bidirectional beamforming scheme. Other secondary users provide a relaying service to the primary users in exchange for the opportunity to send their messages towards their own destinations for a fixed portion of the communication cycle. In addition, it is assumed that some interferers are active during the communication cycle and cause interference for the network. Furthermore, it is assumed that only partial channel state information (CSI) between interferers and other nodes in the network is available.We provide a robust optimization method against imperfection on the interferers' CSI to maximize the joint primary and secondary signal-to-interference-plus-noise-ratio (SINR) with the assumption of limited available power at the secondary relays. An amplify-and-forward (AF) relaying scheme is deployed at the secondary relays and the optimal beamforming is obtained using second order convex programming (SOCP) method. The simulation results show the performance of the proposed beamforming method arXiv:1809.02274v1 [cs.IT]

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“…Cognitive radio systems can be used to mitigate the radiofrequency (RF) spectrum underutilization and hence to cir-cumvent the issues of spectrum scarcity in the next-generation wireless systems [5]. Cognitive radios leverage the concept of opportunistic utilization of the spectrum, in which the licensed spectrum of the primary systems can be accessed and utilized by the unlicensed secondary systems without causing detrimental CCI [5]- [9]. The cognitive radios can access the licensed spectrum of the primary system opportunistically by using underlay, overlay and interweave spectrum sharing techniques [10].…”

Section: Introductionmentioning

confidence: 99%

“…This peak transmit power constraint protects the primary systems by maintaining the detrimental CCI inflicted at the primary receivers to an acceptable level, which is less than a predefined primary interference temperature (PIT) [11]. Prior related research: In [6]- [9], conventional MIMO techniques with small antenna arrays at the base-stations (BSs) are exploited to boost the achievable diversity order or/and spatial multiplexing gains of cognitive radios with spectrum sharing techniques subject to the fundamental diversity-rate trade-off. Recently, massive MIMO techniques have been investigated for cognitive radios with underlay spectrum sharing [12]- [22].…”

Section: Introductionmentioning

confidence: 99%

Multi-Cell Massive MIMO Uplink With Underlay Spectrum Sharing

Al-Hraishawi

Baduge

Ngo

et al. 2019

IEEE Trans. Cogn. Commun. Netw.

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The achievable rates are investigated for multicell multiuser massive multiple-input multiple-output (MIMO) systems with underlay spectrum sharing. A general pilot sharing scheme and two pilot sequence designs (PSDs) are investigated via fully-shared (PSD-1) and partially-shared (PSD-2) uplink pilots. The number of simultaneously served primary users (PUs) and secondary users (SUs) in the same time-frequency resource block by the PSD-1 is higher than that of PSD-2. The transmit power constraints for the SUs are derived to mitigate the secondary co-channel interference (CCI) inflicted at the primary base-station (PBS) subject to a predefined primary interference temperature (PIT). The optimal transmit power control coefficients for the SUs with max-min fairness, and the common achievable rates are derived. The cumulative detrimental effects of channel estimation errors, CCI and intra-cell/inter-cell pilot contamination are investigated. The secondary transmit power constraint and the achievable rates for the perfect channel state information (CSI) case become independent of the PIT when the number of PBS antennas grows unbounded. Therefore, the primary and secondary systems can be operated independent of each other as both intra-cell and inter-cell interference can be asymptotically mitigated at the massive MIMO PBS and secondary base-station (SBS). Nevertheless, the achievable rates and secondary power constraints for the imperfect CSI case with PSD-1 are severely degraded due to the presence of intra-cell and inter-cell pilot contamination. These performance metrics depend on the PIT even in the asymptotic PBS antenna regime. Hence, the primary and secondary systems can no longer be operated independently for imperfect CSI with PSD-1. However, PSD-2 provides achievable rate gains over PSD-1 despite the requirement of lengthier pilot sequences of the former than that of the latter.

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Achievable Rate of Spectrum Sharing Cognitive Radio Multiple-Antenna Channels

Cited by 24 publications

References 29 publications

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

Optimal Relaying Beamforming in Multiple Access Broadcast Channel (MABC) Bidirectional Cognitive Radio Networks in Presence of Interferers

Multi-Cell Massive MIMO Uplink With Underlay Spectrum Sharing

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