A three-dimensional continuous-time Markov model is proposed for an energy harvesting cognitive radio system, where each secondary user (SU) harvests energy from the ambient environment and attempts to transmit data packets on spectrum holes in an infinite queuing buffer. Unlike most previous works, the SU can perform spectrum sensing, data transmission, and energy harvesting simultaneously. We determine active probability of the SU transmitter, where the average energy consumption for both spectrum sensing and data transmission should not exceed the amount of harvested energy. Then, we formulate achievable throughput of secondary network as a convex optimization problem under average transmit and interference energy constraints. The optimal pair of controlled energy harvesting rate and data packet rate is derived for proposed model. Results indicate that no trade-off is available among harvesting, sensing/receiving, and transmitting. The SU capability for self-interference cancelation affects the maximum throughput. We develop this work under hybrid channels including overlay and underlay cases and propose a hybrid solution to achieve the maximum throughput. Simulation results verify that our proposed strategy outperforms the efficiency of the secondary network compared to the previous works. KEYWORDS throughput, optimization, energy harvesting, spectrum sensing, Markov model, self-interference cancelation 1 | INTRODUCTIONDuring recent years, energy harvesting cognitive radio has been emerged as a novel technology to exploit unused spectrum band and energy from the surrounding environment. Opportunistic spectrum access is a practical architecture for discovering spectrum holes and supports the primary user (PU) from harmful interference in a cognitive radio. In many cognitive radio scenarios, the SUs have a battery-power source for sensing spectrum and transmitting data. Energy harvesting offers a useful solution, which allows the SUs to harvest energy from the environmental energy sources such as surrounding radio power, mechanical vibrations, solar, and other natural phenomena.During the last decade, energy crisis has attracted a lot of attention. Renewable energy sources can reduce the prices and the demand for conventional energy supplies. In addition, efficient use of energy is regarded as an important issue for wireless communication services. In order to solve such problems, a lot of works such as energy-efficient protocol design and energy-saving hardware have been implemented. 1,2 Energy harvesting has been considered as promising technology which can store unlimited energy unlike battery-power systems. Furthermore, spectrum scarcity is another prominent problem in wireless communication networks. Dynamic spectrum access technique can improve the network efficiency and simplify the spectrum reuse. It allows the SUs to access the white spaces when the licensed spectrum band is not occupied by the PUs and share the spectrum until the PUs are appropriately protected. 3,4 A large body of research has been c...

Energy harvesting cognitive radio has been considered as a promising technology in the fifth generation (5G) of wireless networks to solve the lack of spectrum and energy. In this paper, a novel wireless energy harvesting relay network is proposed for a multiuser cognitive radio to obtain the maximum throughput and decrease the false alarm and misdetection probabilities. The secondary user (SU) can harvest energy from solar sources while utilizing the licensed spectrum of the primary user (PU). Cooperative spectrum sensing is applied to improve the performance of the secondary network and decrease collision and sensing time. In this paper, the SU can carry out the transmitting, harvesting, and sensing using a full-duplex technique at the same time. Furthermore, we analyze the spectrum sensing of the proposed multiuser network under a data fusion scheme to discover the frequency hole. We demonstrate that the optimization problem can convert into a convex problem and achieve the optimal regulated rate of energy harvesting based on the Lagrangian function. This new network provides improved throughput, precise spectrum sensing, and high energy harvesting compared to the existing works studied so far. Finally, we verify the efficiency of the proposed method via simulation results and show that the optimal regulated rate is determined based on the priority of given constraints. the frequency band when the primary users (PUs) give up the channel [1][2][3]. A general summary of radio frequency energy harvesting systems was discussed in [4], including new research, system architecture, useful techniques, and available applications. Additionally, the applications of radio frequency energy harvesting are investigated in different networks, such as wireless sensor networks [5] and wireless charging networks [6]. An optimal cooperation protocol was proposed for an energy harvesting cognitive radio system in [7] to maximize the achievable throughput and provide the optimal decision, which consists of a two-level test. Furthermore, the average throughput was formulated under collision and energy constraints in [8] in order to achieve the optimal sensing time and threshold of the energy detector.Relay technology was investigated for cognitive radio networks in [9][10][11][12]. In [13], the effect of relaying * Correspondence: hfarrokhi@birjand.ac.ir This work is licensed under a Creative Commons Attribution 4.0 International License.

The rapid time-variation of a fading multipath environment can impair the performance of multiple-input multiple-output orthogonal frequency division multiplexing (MIMO OFDM). This paper proposes a pilot placement method for MIMO OFDM systems under time-varying channels with the guard band. The time-varying channel is described by complex exponential basis expansion model (BEM). We discuss the least square (LS) channel estimation to obtain the minimum mean square error (MSE) and derive the pilot allocation that can satisfy the minimum MSE with regard to guard band in time-varying channels. It is shown that optimal pilot clusters can distribute non-uniformly in frequency domain and minimize the MSE. We generalize our scheme over G OFDM symbols and compare it with comb pilots. It is demonstrated that the proposed approach is more effective than previous work. Simulation results validate our theoretical analysis

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