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In this paper, we consider a cognitive radio (CR) system consisting of a primary user (PU) and a pair of secondary user transmitter (SUtx) and secondary user receiver (SUrx). The SUtx is equipped with a reconfigurable antenna (RA) which divides the angular space into M sectors. The RA chooses one sector among M sectors for its data transmission to SUrx. The SUtx first senses the channel and monitors the activity of PU for a duration of Tsen seconds. We refer to this period as channel sensing phase. Depending on the outcome of this phase, SUtx stays in this phase or enters the next phase, which we refer to as transmission phase. The transmission phase itself consists of two phases: channel training phase followed by data transmission phase. During the former phase, SUtx sends pilot symbols to enable channel training and estimation at SUrx. The SUrx selects the best beam (sector) for data transmission and feeds back the index of the selected beam as well as its corresponding channel gain. We also derive the probability of determining the true beam and take into account this probability in our system design. During the latter phase, SUtx sends data symbols to SUrx over the selected beam with constant power Φ if the gain corresponding to the selected beam is bigger than the threshold ζ. We find the optimal channel sensing duration Tsen, the optimal power level Φ and a optimal threshold ζ, such that the ergodic capacity of CR system is maximized, subject to average interference and power constraints. In addition, we derive closed form expressions for outage and symbol error probabilities of our CR system.

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.

We consider a cognitive radio system, consisting of a primary transmitter (PUtx), a primary receiver (PUrx), a secondary transmitter (SUtx), and a secondary receiver (SUrx). The secondary users (SUs) are equipped with steerable directional antennas. We assume the SUs and primary users (PUs) coexist and the SUtx knows the geometry of network. We find the ergodic capacity of the channel between SUtx and SUrx, and study how spectrum sensing errors affect the capacity. In our system, the SUtx first senses the spectrum and then transmits data at two power levels, according to the result of sensing. The optimal SUtx transmit power levels and the optimal directions of SUtx transmit antenna and SUrx receive antenna are obtained by maximizing the ergodic capacity, subject to average transmit power and average interference power constraints. To study the effect of fading channel, we considered three scenarios: 1) when SUtx knows fading channels between SUtx and PUrx, PUtx and SUrx, SUtx and SUrx, 2) when SUtx knows only the channel between SUtx and SUrx, and statistics of the other two channels, and, 3) when SUtx only knows the statistics of these three fading channels. For each scenario, we explore the optimal SUtx transmit power levels and the optimal directions of SUtx and SUrx antennas, such that the ergodic capacity is maximized, while the power constraints are satisfied.

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We consider a wireless sensor network, consisting of N heterogeneous sensors and a fusion center (FC), that is tasked with solving a binary distributed detection problem. Each sensor is capable of harvesting randomly arrived energy and storing it in a finite capacity battery. Sensors are informed of their fading channel states, via a bandwidth-limited feedback channel from the FC. Each sensor has the knowledge of its current battery state and its channel state (quantized channel gain). Our goal is to study how sensors should choose their transmit powers such that J-divergence of the received signal densities under two hypotheses at the FC is maximized, subject to certain (battery and power) constraints. We derive the optimal power map, which depends on the energy arrival rate, the battery capacity, and the battery states probabilities at the steady state. Using the optimal power map, each sensor optimally adapts its transmit power, based on its battery state and its channel state. Our simulation results demonstrate the performance of our proposed power adaptation scheme for different system parameters.

We consider a cognitive radio system, in which the secondary users (SUs) and primary users (PUs) coexist. The SUs are equipped with steerable directional antennas. In our system, the secondary transmitter (SUtx) first senses the spectrum (with errors) for a duration of τ , and, then transmits data to the secondary receiver (SUrx) if spectrum is sensed idle. The sensing time as well as the orientation of SUtx's antenna affect the accuracy of spectrum sensing and yield a trade-off between spectrum sensing and capacity of the secondary network. We formulate the ergodic capacity of secondary network which uses energy detection for spectrum sensing. We obtain optimal SUtx transmit power, the optimal sensing time τ and the optimal directions of SUtx transmit antenna and SUrx receive antenna by maximizing the ergodic capacity, subject to peak transmit power and outage interference probability constraints. Our simulation results show the effectiveness of these optimizations to increase the ergodic capacity of the secondary network.

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