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In this paper, we first explore a selective cooperation framework for secondary user transmissions in a cognitive radio network with single relay. In the selective cooperation framework, two transmission modes (i.e., relay diversity transmission and non-relay direct transmission) are considered. We study two specific selective cooperation schemes with and without an acknowledgement (ACK) from a cognitive destination as to if it succeeds in decoding or not, called ACK and non-ACK based selective cooperation, respectively. We derive closed-form outage probability expressions for the two schemes with imperfect spectrum sensing, showing that an outage probability floor occurs in high signal-to-noise ratio (SNR) regions due to mutual interference between primary and secondary users. We consider the use of the outage probability floor to generalize the traditional diversity-multiplexing tradeoff (DMT) definition, based on which a DMT analysis is conducted for the non-ACK and ACK based selective cooperation schemes. We then extend the selective cooperation framework to a multiple-relay cognitive radio network considering the best cognitive relay only to participate in assisting secondary transmissions, referred to as the selective best-relay cooperation. We also consider the non-ACK and ACK based selective best-relay cooperation schemes and develop their DMTs by using the generalized DMT definition. [ABSTRACT FROM PUBLISHER]

This paper investigates the problem of energy efficiency maximization (EEM) for the small cells that coexist with a macro cell in an underlay heterogeneous cellular network, where a macro base station and a number of small base stations transmit signals to a macro user and small users through their shared spectrum. We propose a joint power and bandwidth allocation (JPBA) scheme for the sake of maximizing the energy efficiency (EE) of small cells under the constraint of a guaranteed quality-of-service requirement for the macro cell. Considering that our formulated EEM-based JPBA (EEM-JPBA) problem is non-convex, we convert the original fractional problem into an equivalent subtractive form by adopting the Dinkelbach’s method, which is addressed through the augmented Lagrange multiplier approach. Moreover, a new two-tier iterative algorithm is presented to obtain the optimal solution of our EEM-JPBA scheme. Simulation results demonstrate that the proposed two-tier iterative algorithm can quickly converge to the optimal EE solution. In addition, it is shown that the proposed EEM-JPBA scheme significantly outperforms the conventional power and bandwidth allocation methods in terms of their EE performance. [ABSTRACT FROM AUTHOR]

In this paper, we study a multiuser uplink network consisting of one base station (BS), multiple users and one eavesdropper (E), where the users are intended to transmit their confidential messages to BS, while the eavesdropper attempts to tap their transmissions. To improve the transmission secrecy, we propose two friendly jammer selection-aided multiuser scheduling schemes, namely, the random jammer selection-aided multiuser scheduling (RJS-MUS) without knowing the eavesdropper’s channel state information (CSI) and the optimal jammer selection-aided multiuser scheduling (OJS-MUS), where the CSIs of eavesdropper are available. For comparison purposes, the conventional non-jammer selection-aided multiuser scheduling (NJS-MUS) scheme is considered as a benchmark. We derive exact and asymptotic closed-form secrecy outage probability expressions for the conventional NJS-MUS as well as proposed RJS-MUS and OJS-MUS schemes. The numerical results show that the proposed RJS-MUS and OJS-MUS schemes with equal power allocation between the selected friendly jammer and scheduled user perform worse than the conventional NJS-MUS approach in terms of the secrecy outage probability in the low signal-to-noise ratio (SNR) region. As the SNR increases, the secrecy outage performance of RJS-MUS and OJS-MUS schemes substantially improves, which is, in turn, better than that of conventional NJS-MUS approach. Moreover, the secrecy advantage of RJS-MUS and OJS-MUS over NJS-MUS becomes more significant with an increasing SNR. Also, it is shown that for both the RJS-MUS and OJS-MUS schemes, a better secrecy performance can be achieved through an optimal power allocation (OPA) between the scheduled user and friendly jammer. In addition, the proposed RJS-MUS and OJS-MUS schemes with OPA strictly outperform the conventional NJS-MUS approach in terms of the secrecy outage probability. [ABSTRACT FROM AUTHOR]

This paper investigates the issue of cooperative spectrum sensing with a crowd of low-end personal spectrum sensors (such as smartphones, tablets, and in-vehicle sensors), where the sensing data from crowd sensors that may be unreliable, untrustworthy, or even malicious. Moreover, due to either unexpected equipment failures or malicious behaviors, every crowd sensor could sporadically and randomly contribute with abnormal data, which makes the existing cooperative sensing schemes ineffective. To tackle these challenges, we first propose a generalized modeling approach for sensing data with an arbitrary abnormal component. Under this model, we then analyze the impact of general abnormal data on the performance of the cooperative sensing, by deriving closed-form expressions of the probabilities of global false alarm and global detection. To improve sensing data quality and enhance cooperative sensing performance, we further formulate an optimization problem as stable principal component pursuit, and develop a data cleansing-based robust spectrum sensing algorithm to solve it, where the under-utilization of licensed spectrum bands and the sparsity of nonzero abnormal data are jointly exploited to robustly cleanse out the potential nonzero abnormal data component from the original corrupted sensing data. Extensive simulation results demonstrate that the proposed robust sensing scheme performs well under various abnormal data parameter configurations. [ABSTRACT FROM PUBLISHER]