Energy Efficient Power Allocation for OFDM-Based Cognitive Radio Systems with Partial Intersystem CSI

This paper investigates energy efficient power allocation for orthogonal frequency division multiplexing- (OFDM-) based cognitive radio (CR) systems with partial intersystem channel state information (CSI) available. The goal is to maximize energy efficiency (EE) while ensuring the minimum rate of secondary user (SU) and keeping the average interference power (AIP) introduced to primary user (PU) within a target probability level. We propose a suboptimal algorithm to solve this optimization problem based on classic water-filling (WF) technique. Moreover, we first address the relation between EE and water level. In order to reduce complexity, a simplified algorithm with closed-form solution is also proposed. Numerical results are provided to corroborate our theoretical analysis and to demonstrate the effectiveness of the proposed schemes

Deletion of a 197-Amino-Acid Region in the N-Terminal Domain of Spike Protein Attenuates Porcine Epidemic Diarrhea Virus in Piglets

ABSTRACT We previously isolated a porcine epidemic diarrhea virus (PEDV) strain, PC177, by blind serial passaging of the intestinal contents of a diarrheic piglet in Vero cell culture. Compared with the highly virulent U.S. PEDV strain PC21A, the tissue culture-adapted PC177 (TC-PC177) contains a 197-amino-acid (aa) deletion in the N-terminal domain of the spike (S) protein. We orally inoculated neonatal, conventional suckling piglets with TC-PC177 or PC21A to compare their pathogenicities. Within 7 days postinoculation, TC-PC177 caused mild diarrhea and lower fecal viral RNA shedding, with no mortality, whereas PC21A caused severe clinical signs and 55% mortality. To investigate whether infection with TC-PC177 can induce cross-protection against challenge with a highly virulent PEDV strain, all the surviving piglets were challenged with PC21A at 3 weeks postinoculation. Compared with 100% protection in piglets initially inoculated with PC21A, 88% and 100% TC-PC177- and mock-inoculated piglets had diarrhea following challenge, respectively, indicating incomplete cross-protection. To investigate whether this 197-aa deletion was the determinant for the attenuation of TC-PC177, we generated a mutant (icPC22A-S1Δ197) bearing the 197-aa deletion from an infectious cDNA clone of the highly virulent PEDV PC22A strain (infectious clone PC22A, icPC22A). In neonatal gnotobiotic pigs, the icPC22A-S1Δ197 virus caused mild to moderate diarrhea, lower titers of viral shedding, and no mortality, whereas the icPC22A virus caused severe diarrhea and 100% mortality. Our data indicate that deletion of this 197-aa fragment in the spike protein can attenuate a highly virulent PEDV, but the virus may lose important epitopes for inducing robust protective immunity. IMPORTANCE The emerging, highly virulent PEDV strains have caused substantial economic losses worldwide. However, the virulence determinants are not established. In this study, we found that a 197-aa deletion in the N-terminal region of the S protein did not alter virus (TC-PC177) tissue tropism but reduced the virulence of the highly virulent PEDV strain PC22A in neonatal piglets. We also demonstrated that the primary infection with TC-PC177 failed to induce complete cross-protection against challenge by the highly virulent PEDV PC21A, suggesting that the 197-aa region may contain important epitopes for inducing protective immunity. Our results provide an insight into the role of this large deletion in virus propagation and pathogenicity. In addition, the reverse genetics platform of the PC22A strain was further optimized for the rescue of recombinant PEDV viruses in vitro . This breakthrough allows us to investigate other virulence determinants of PEDV strains and will provide knowledge leading to better control PEDV infections

A Distributed Learning Method for ℓ 1 -Regularized Kernel Machine over Wireless Sensor Networks

In wireless sensor networks, centralized learning methods have very high communication costs and energy consumption. These are caused by the need to transmit scattered training examples from various sensor nodes to the central fusion center where a classifier or a regression machine is trained. To reduce the communication cost, a distributed learning method for a kernel machine that incorporates ℓ 1 norm regularization ( ℓ 1 -regularized) is investigated, and a novel distributed learning algorithm for the ℓ 1 -regularized kernel minimum mean squared error (KMSE) machine is proposed. The proposed algorithm relies on in-network processing and a collaboration that transmits the sparse model only between single-hop neighboring nodes. This paper evaluates the proposed algorithm with respect to the prediction accuracy, the sparse rate of model, the communication cost and the number of iterations on synthetic and real datasets. The simulation results show that the proposed algorithm can obtain approximately the same prediction accuracy as that obtained by the batch learning method. Moreover, it is significantly superior in terms of the sparse rate of model and communication cost, and it can converge with fewer iterations. Finally, an experiment conducted on a wireless sensor network (WSN) test platform further shows the advantages of the proposed algorithm with respect to communication cost

Energy Efficient Design for OFDM-Based Underlay Cognitive Radio Networks

Conventional designs on OFDM-based underlay cognitive radio (CR) networks mainly focus on interference avoidance and spectral efficiency (SE) improvement. As green radio becomes increasingly important, this paper investigates energy efficient power allocation. Our aim is to maximize energy efficiency (EE), subject to the constraints on the total transmit power, the peak interference power, and the minimum data rate requirement. We first analyze the relationship between SE and EE and solve this optimization problem with the help of bisection search technique. However, the accuracy of the power allocation solution is dependent on the number of iterations. In order to achieve the exact optimal solution, a new energy efficient power allocation scheme is proposed to balance the tradeoff between SE and EE. Simulation results are provided to demonstrate the effectiveness of the proposed schemes