On Optimal Sensing and Capacity Trade-off in Cognitive Radio Systems with Directional Antennas

Yazdani, Hassan; Vosoughi, Azadeh

doi:10.1109/globalsip.2018.8646661

Cited by 8 publications

(6 citation statements)

References 15 publications

(18 reference statements)

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“…Utilizing ESPAR antennas for opportunistic spectrum sharing systems is a highly promising solution to enhance the performance of secondary links, while satisfying the constraints set by the primary links [28]. • This work is different from our preliminary works in [33]- [35], where we have considered a simpler constrained optimization problem (with different optimization variables, including continuous transmit power and direction of antenna steering of SU tx ), assuming that SU tx knows the direction (angle) corresponding to PU's activities. It is also different from our work in [1], where we have assumed that SU tx knows the location of SU rx and PU, and, perfect CSI of SU tx -SU rx link is available and used for transmit power adaptation.…”

Section: F Our Contributions and Paper Organizationmentioning

confidence: 92%

Beam Selection and Discrete Power Allocation in Opportunistic Cognitive Radio Systems With Limited Feedback Using ESPAR Antennas

Yazdani

Vosoughi

Gong

2020

IEEE Trans. Cogn. Commun. Netw.

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We consider an opportunistic cognitive radio (CR) system consisting of a primary user (PU), secondary transmitter (SUtx), and secondary receiver (SUrx), where SUtx is equipped with an electrically steerable parasitic array radiator (ESPAR) antenna with beam steering capability for sensing and communication, and there is a limited feedback channel from SUrx to SUtx. Taking a holistic approach, we develop a framework for integrated sector-based spectrum sensing and sector-based data communication. Upon sensing the channel busy, SUtx determines the beam corresponding to PU's orientation. Upon sensing the channel idle, SUtx transmits data to SUrx, using the selected beam corresponding to the strongest channel between SUtx and SUrx. We formulate a constrained optimization problem, where SUtx-SUrx link ergodic capacity is maximized, subject to average transmit power and interference constraints, and the optimization variables are sensing duration, thresholds of channel quantizer at SUrx, and transmit power levels at SUtx. Since this problem is non-convex we develop a suboptimal computationally efficient iterative algorithm to find the solution. Our numerical results quantify the capacity improvement provided by the ESPAR antenna and demonstrate that our CR system yields lower outage and symbol error probabilities, compared with a CR system that its SUtx has an omni-directional antenna.Index Terms-Beam selection, cognitive radio, constrained ergodic capacity maximization, discrete power allocation, ESPAR antenna, imperfect channel sensing, error-free bandwidth limited feedback channel, reconfigurable antennas.

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Section: F Our Contributions and Paper Organizationmentioning

confidence: 92%

Beam Selection and Discrete Power Allocation in Opportunistic Cognitive Radio Systems With Limited Feedback Using ESPAR Antennas

Yazdani

Vosoughi

Gong

2020

IEEE Trans. Cogn. Commun. Netw.

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“…For large N s , we can invoke central limit theorem and approximate the cumulative distribution function (CDF) of Z n as Guassian. Hence, P fan and P dn can be expressed in terms of Q function as below [36]…”

Section: Transmission Model and Battery Dynamicsmentioning

confidence: 99%

Steady-State Rate-Optimal Power Adaptation in Energy Harvesting Opportunistic Cognitive Radios With Spectrum Sensing and Channel Estimation Errors

Yazdani¹,

Vosoughi²

2021

IEEE Trans. on Green Commun. Netw.

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We consider an uplink cognitive radio (CR) network that can access a wideband spectrum licensed to a primary network, which is divided into non-overlapping narrowband channels. The secondary users (SUs) are equipped with rechargeable battery of finite capacity that solely powered by energy harvesting from the ambient environment. The SUs which are aware of the available energy in their batteries, sense the activity of the primary transmitter. If the result of spectrum sensing is idle, SUs send pilot symbols to the secondary access point (AP) and AP estimates the secondary channel power. Then, AP feeds back the channel gain to SUs. Knowing the battery state and the feedback information, SUs optimally adapt their transmit power to AP such that the steady-state sum rate of SU-AP link is maximized, subject to average interference constraint (AIC) imposed on the primary receiver and the causality constraint of the batteries. We illustrate the effect of the AIC, energy arrival rate and battery capacity on the steady state distribution of battery, CR network rate, battery energy outage probability and transmission outage probability via simulation.

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“…In opportunistic CR systems, spectrum sensing is necessary for detecting PUs' activities and protecting the PUs against harmful interference. In general, any spectrum sensing (signal in noise detection) technique is prone to errors, that can be described as mis-detection or false alarm probability [11], [12]. On the other hand, imperfect CSI of SU tx -SU rx link due to channel estimation error (even under perfect spectrum sensing) has negative influence on the link capacity.…”

Section: Introduction a Literature Reviewmentioning

confidence: 99%

Achievable Rates of Opportunistic Cognitive Radio Systems Using Reconfigurable Antennas with Imperfect Sensing and Channel Estimation

Yazdani

Vosoughi

Gong

2020

Preprint

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We consider an opportunistic cognitive radio (CR) system in which secondary transmitter (SUtx) is equipped with a reconfigurable antenna (RA). Utilizing the beam steering capability of the RA, we regard a design framework for integrated sector-based spectrum sensing and data communication. In this framework, SUtx senses the spectrum and detects the beam corresponding to active primary user's (PU) location. SUtx also sends training symbols (prior to data symbols), to enable channel estimation at secondary receiver (SUrx) and selection of the strongest beam between SUtx-SUrx for data transmission. We establish a lower bound on the achievable rates of SUtx-SUrx link, in the presence of spectrum sensing and channel estimation errors, and errors due to incorrect detection of the beam corresponding to PU's location and incorrect selection of the strongest beam for data transmission. We formulate a novel constrained optimization problem, aiming at maximizing the derived achievable rate lower bound subject to average transmit and interference power constraints. We optimize the durations of spatial spectrum sensing and channel training as well as data symbol transmission power. Our numerical results demonstrate that between optimizing spectrum sensing and channel training durations, the latter is more important for providing higher achievable rates.

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On Optimal Sensing and Capacity Trade-off in Cognitive Radio Systems with Directional Antennas

Cited by 8 publications

References 15 publications

Beam Selection and Discrete Power Allocation in Opportunistic Cognitive Radio Systems With Limited Feedback Using ESPAR Antennas

Beam Selection and Discrete Power Allocation in Opportunistic Cognitive Radio Systems With Limited Feedback Using ESPAR Antennas

Steady-State Rate-Optimal Power Adaptation in Energy Harvesting Opportunistic Cognitive Radios With Spectrum Sensing and Channel Estimation Errors

Achievable Rates of Opportunistic Cognitive Radio Systems Using Reconfigurable Antennas with Imperfect Sensing and Channel Estimation

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