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Register a new userPractical Design for Multiple-Antenna Cognitive Radio Networks with Coexistence Constraint
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Pin-Hsun Lin
Publication date
2013
fields
Informatics Engineering
and research's language is
English
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In this paper we investigate the practical design for the multiple-antenna cognitive radio (CR) networks sharing the geographically used or unused spectrum. We consider a single cell network formed by the primary users (PU), which are half-duplex two-hop relay channels and the secondary users (SU) are single user additive white Gaussian noise channels. In addition, the coexistence constraint which requires PUs coding schemes and rates unchanged with the emergence of SU, should be satisfied. The contribution of this paper are twofold. First, we explicitly design the scheme to pair the SUs to the existing PUs in a single cell network. Second, we jointly design the nonlinear precoder, relay beamformer, and the transmitter and receiver beamformers to minimize the sum mean square error of the SU system. In the first part, we derive an approximate relation between the relay ratio, chordal distance and strengths of the vector channels, and the transmit powers. Based on this relation, we are able to solve the optimal pairing between SUs and PUs efficiently. In the second part, considering the feasibility of implementation, we exploit the Tomlinson-Harashima precoding instead of the dirty paper coding to mitigate the interference at the SU receiver, which is known side information at the SU transmitter. To complete the design, we first approximate the optimization problem as a convex one. Then we propose an iterative algorithm to solve it with CVX. This joint design exploits all the degrees of design. To the best of our knowledge, both the two parts have never been considered in the literature. Numerical results show that the proposed pairing scheme outperforms the greedy and random pairing with low complexity. Numerical results also show that even if all the channel matrices are full rank, under which the simple zero forcing scheme is infeasible, the proposed scheme can still work well.
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Cognitive radio networks (CRNs) and millimeter wave (mmWave) communications are two major technologies to enhance the spectrum efficiency (SE). Considering that the SE improvement in the CRNs is limited due to the interference temperature imposed on the primary user (PU), and the severe path loss and high directivity in mmWave communications make it vulnerable to blockage events, we introduce an intelligent reflecting surface (IRS) into mmWave CRNs. This paper investigates the robust secure beamforming (BF) design in the IRS-assisted mmWave CRNs. By using a uniform linear array (ULA) at the cognitive base station (CBS) and a uniform planar array (UPA) at the IRS, and supposing that the imperfect channel state information (CSI) of wiretap links is known, we formulate a constrained problem to maximize the worst-case achievable secrecy rate (ASR) of the secondary user (SU) by jointly designing the transmit BF at the CBS and reflect BF at the IRS. To solve the non-convex problem with coupled variables, an efficient alternating optimization algorithm is proposed. As for the transmit BF at the CBS, we propose a heuristic robust transmit BF algorithm to attain the BF vectors analytically. As for the reflect BF at the IRS, by means of an auxiliary variable, we transform the non-convex problem into a semi-definite programming (SDP) problem with rank-1 constraint, which is handled with the help of an iterative penalty function, and then obtain the optimal reflect BF through CVX. Finally, the simulation results indicate that the ASR performance of our proposed algorithm has a small gap with that of the optimal solution with perfect CSI compared with the other benchmarks.
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In wireless data networks, communication is particularly susceptible to eavesdropping due to its broadcast nature. Security and privacy systems have become critical for wireless providers and enterprise networks. This paper considers the problem of secret communication over the Gaussian broadcast channel, where a multi-antenna transmitter sends independent confidential messages to two users with perfect secrecy. That is, each user would like to obtain its own message reliably and confidentially. First, a computable Sato-type outer bound on the secrecy capacity region is provided for a multi-antenna broadcast channel with confidential messages. Next, a dirty-paper secure coding scheme and its simplified version are described. For each case, the corresponding achievable rate region is derived under the perfect secrecy requirement. Finally, two numerical examples demonstrate that the Sato-type outer bound is consistent with the boundary of the simplified dirty-paper coding secrecy rate region.
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Blind Null Space Learning (BNSL) has recently been proposed for fast and accurate learning of the null-space associated with the channel matrix between a secondary transmitter and a primary receiver. In this paper we propose a channel tracking enhancement of the algorithm, namely the Blind Null Space Tracking (BNST) algorithm that allows transmission of information to the Secondary Receiver (SR) while simultaneously learning the null-space of the time-varying target channel. Specifically, the enhanced algorithm initially performs a BNSL sweep in order to acquire the null space. Then, it performs modified Jacobi rotations such that the induced interference to the primary receiver is kept lower than a given threshold $P_{Th}$ with probability $p$ while information is transmitted to the SR simultaneously. We present simulation results indicating that the proposed approach has strictly better performance over the BNSL algorithm for channels with independent Rayleigh fading with a small Doppler frequency.
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