In cognitive radio systems, cooperative spectrum sensing can detect the presence of the primary user accurately. In practice, however, since the sensing observations are forwarded to a data collector through fading channels, the sensing performance is severely degraded. To deal with this problem, in this paper, we first propose a secondary user selection based cooperative spectrum sensing method to improve sensing performance by decreasing the reporting errors introduced by the fading channels. More specifically, only the secondary users with better signal-to-noise ratio (SNR) for reporting channels are allowed to send their local binary decisions (0 or 1) to the data collector while the others will send nothing. Additionally, we further propose a diversity based cooperative spectrum sensing method which applies existing space-time coding. By exploiting space diversity in CR network, the reporting errors introduced by the fading channel can be decreased and then the sensing performance is improved significantly. For either proposed cooperative spectrum sensing method, the sensing performance is derived and the analytical performance results are given. Our analysis and numerical results verify that proposed methods outperform the conventional cooperative spectrum sensing with OR-rule by taking into account the error effect on the reporting channels. CitationYue W J, Zheng B Y, Meng Q M, et al. Robust cooperative spectrum sensing schemes for fading channels in cognitive radio networks.

This paper proposes a low complexity channel estimation algorithm for unmanned aerial vehicle three dimension multi-user multiple-input-multiple-output (3D MIMO) systems with the uniform planar array (UPA) at base station using paired spatial signatures. With the aid of antenna array theory and array signal processing, 3D channel is firstly modeled based on the angles between the direction of arrival along x- and y-axis of the UPA. And 3D MIMO channels can be projected onto the x- and y-directions, respectively. Then, channel estimation for multi-user uplinks using small amount of training resources is divided into two phases. At the first uplink preamble phase, each user is assigned the orthogonal pilot, and the paired spatial signatures and optimal rotation angle of each user through the same pilot sequence are obtained. We also propose a user grouping strategy based on three-dimension angle-division multiple access (3D-ADMA) to ensure that the user's spatial signatures do not overlap. At the second phase during several coherence times, the same pilot sequence within a group and orthogonal pilot sequences between groups are assigned, then, the channel state information of the user's x- and y-directions are recovered by the paired space signatures and optimal rotation angle of each user obtained in the preamble phase, respectively. And dynamically updating the user's paired spatial signatures and optimal rotation angle utilizes the obtained channel parameter of x- and y-directions. Finally, the channel parameter of the x- and y-directions are reconstructed by the updated user's space signatures and the optimal rotation angle, and the 3D MIMO channel estimation is obtained through the Kronecker product. Compared with the conventional channel estimation method of the 3D MIMO system under UPA using a low-rank model, the proposed methods reduce the computational complexity without degrading the estimated performance to a large extent. Furthermore, it is carried out with limited training resources, and the pilot resource overhead of the system is greatly reduced by the 3D-ADMA packet and the two-stage pilot allocation. Simulation results verified that the proposed algorithm is effective and feasible.

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Abstract：A cognitive relay network model is proposed, which is defined by a source, a destination, a cognitive relay node and a primary user. The source is assisted by the cognitive relay node which is allowed to coexist with the primary user by imposing severe constraints on the transmission power so that the quality of service of the primary user is not degraded by the interference caused by the secondary user. The effect of the cognitive relay node on the proposed cognitive relay network model is studied by evaluating the outage probability under interference power constraints for different fading environments. A relay transmission scheme, namely, decode-and-forward is considered. For both the peak and average interference power constraints, the closed-form outage expressions are derived over different channel fading models. Finally, the analytical outage probability expressions are validated through simulations. The results indicate that the proposed model has better outage probability than direct transmission. It is also found that the outage probability decreases with the increase of interference power constraints. Meanwhile, the outage probability under the average interference power constraint is much less than that under the peak interference power constraint when the average interference power constraint is equal to the peak interference power constraint. Keywords：cognitive radio; relay networks; outage probability; power control With the rapid growth of wireless communication, the demand for radio spectrum is expected to grow rapidly in the near future. However, radio spectrum is a limited resource and is already crowded. It is difficult to accommodate more wireless applications within this limited resource. On the other hand, the licensed spectrum bands are under-utilized due to the current inflexible spectrum allocation policy [1] .To deal with the conflicts between spectrum congestion and spectrum under-utilization, cognitive radio [2] is a promising technique to improve the spectrum utilization by either allowing a secondary user (SU) to opportunistically operate in the frequency bands originally allocated to a primary user (PU) or by allowing an SU to coexist with a PU as long as the quality of service (QoS) of the PU is not degraded by the interference caused by the SU [3] . However, in overlay scenario, to precisely detect a spectrum hole which is not being used is a tough job.Different from spectrum overlay, the underlay approach does not necessarily rely on the detection and exploitation of spectrum white space, but rather on the transmission power of SUs so as not to cause any harmful interference to the active PUs.Future wireless networks will continue to evolve towards allowing mobile nodes to communicate without the need of infrastructure while providing more reliability and capacity increase. To that end, relay communications have emerged as a powerful spatial diversity technique that can improve the performance over conventional point-to-point transmissions, which has received more and ...

This paper proposes a low complexity channel estimation algorithm for unmanned aerial vehicle (UAV) three dimension multi-user multiple-input-multiple-output (3D MIMO) systems with the uniform planar array (UPA) at base station (BS) using paired spatial signatures. With the aid of antenna array theory and array signal processing, firstly 3D channel modeling based on the angle between the direction of arrival (DOA) and the x- direction of the array antenna, and the angle between the DOA and the y- direction of the array antenna. And 3D MIMO channels can be projected onto the x- and y-directions, respectively. Then, channel estimation for multiuser uplinks using small amount of training resources, which is divided into two phases. The first phase is the uplink preamble phase, which assigns each user an orthogonal pilot, and obtains the paired spatial signatures and optimal rotation angle of each user through the same pilot sequence. We also propose a user grouping strategy based on three dimension angle-division multiple access (3D-ADMA) to ensure that the user's spatial signatures do not overlap. The second phase is much coherence times after the preamble phase, which assigns the same pilot sequence within a group and assigns orthogonal pilot sequences between groups, and the channel state information of the user's x- and y-directions is recovered by the paired space signatures and optimal rotation angle of each user obtained in the preamble phase, respectively. And dynamically updating the user's paired spatial signatures and optimal rotation angle utilizes the obtained channel components of x- and y-directions. Finally, the channel components of the x- and y-directions are reconstructed by the updated user's space signatures and the optimal rotation angle, and the 3D MIMO channel is generated by the Kronecker product. Compared with the conventional channel estimation method of a 3D MIMO system under UPA using a low rank model, the proposed methods greatly reduce the computational complexity without reducing the estimated performance, it is carried out with limited training resources, and the pilot resource overhead of the system is greatly reduced by the 3D-ADMA packet and the two-stage pilot allocation. Various numerical results are provided to corroborate the proposed studies.