Disentangled Feature Learning for Noise-Invariant Speech Enhancement

Most of the recently proposed deep learning-based speech enhancement techniques have focused on designing the neural network architectures as a black box. However, it is often beneficial to understand what kinds of hidden representations the model has learned. Since the real-world speech data are drawn from a generative process involving multiple entangled factors, disentangling the speech factor can encourage the trained model to result in better performance for speech enhancement. With the recent success in learning disentangled representation using neural networks, we explore a framework for disentangling speech and noise, which has not been exploited in the conventional speech enhancement algorithms. In this work, we propose a novel noise-invariant speech enhancement method which manipulates the latent features to distinguish between the speech and noise features in the intermediate layers using adversarial training scheme. To compare the performance of the proposed method with other conventional algorithms, we conducted experiments in both the matched and mismatched noise conditions using TIMIT and TSPspeech datasets. Experimental results show that our model successfully disentangles the speech and noise latent features. Consequently, the proposed model not only achieves better enhancement performance but also offers more robust noise-invariant property than the conventional speech enhancement techniques

Sum-Rate Maximization for Multiuser MIMO Wireless Powered Communication Networks

This paper investigates multiuser multiple-input-multiple-output (MIMO) wireless powered communication networks where a multiantenna hybrid access point (H-AP) transfers wireless energy to multiantenna users in a downlink phase, and the users utilize the harvested energy for their information transmission to the H-AP in an uplink phase. By employing space-division multiple-access techniques, we propose an optimal algorithm that jointly computes the downlink energy precoding matrices, the uplink information precoding matrices, and time allocation between the downlink and the uplink phases for maximizing the uplink sum-rate performance. To this end, we first obtain the optimal energy and information transmit covariance matrices with given time allocation. Then, the optimal time allocation can be efficiently identified by a simple line search method. Simulation results verify that the proposed joint optimal algorithm significantly improves the average sum-rate performance, compared with a conventional scheme that determines time allocation and precoding matrices separately

Joint Subcarrier and Power Allocation Method in Wireless Powered Communication Networks for OFDM Systems

We investigate wireless powered communication network for OFDM systems, where a hybrid access point (H-AP) broadcasts energy signals to users in the downlink, and the users transmit information signals to the H-AP in the uplink based on an orthogonal frequency division multiple access scheme. We consider a full-duplex H-AP which simultaneously transmits energy signals and receives information signals, and a perfect self-interference cancelation where the H-AP fully eliminates its self interference. In this scenario, we address a joint subcarrier scheduling and power allocation problem to maximize the sum-rate. In general, the problem is on-convex due to subcarrier scheduling, and thus it requires an exhaustive search method, which is prohibitively complicated to obtain the globally optimal solution. In order to reduce the complexity, we jointly optimize subcarrier scheduling and power allocation by applying the Lagrange duality method. Simulation results show that the proposed algorithm exhibits only negligible sum-rate performance loss compared to the optimal exhaustive search algorithm and a significant performance gain over conventional scheme

Effects of Humic Acid and Blueberry Leaf Powder Supplementation in Feeds on the Productivity, Blood and Meat Quality of Finishing Pigs

The objective of this study was to determine effects of humic acid (HA) and blueberry leaf powder (BLP) supplementation in pig feed on productivity, blood profiles, and meat quality characteristics of longissimus muscle. The experimental design included six treatments: 1) CON, no addition; 2) T1, BLP 0.1%; 3) T2, BLP 0.2%; 4) T3, humic acid 2%; 5) T4: humic acid 2%+ BLP 0.1%; and 6) T5: humic acid 2%+ BLP 0.2%. HA and BLP supplementation in pig feed significantly increased average daily feed intake (ADFI) values (p<0.05). HA supplementation in pig feed had beneficial effects in lipid profiles without altering feed efficiency rate (FER). HA and BLP co-supplementation in pig feed decreased pH in longissimus thoracis (p<0.05). In addition, sensory characteristics were enhanced when pig feed was supplemented with HA and BLP without causing adverse effects in meat quality. Taken together, addition of HA and BLP in pig feed may produce functional meat products

Optimal Beamforming Designs for Wireless Information and Power Transfer in MISO Interference Channels

This paper investigates the optimal transmit beam-forming designs for simultaneous wireless information and power transfer (SWIPT) in multiple-input single-output interference channels (IFC). Based on cooperation level among transmitters and receivsers, we classify the SWIPT IFC systems into two categories. First, we consider the IFC with partial cooperation, where only channel state information (CSI) is available at transmitters and receivers, but not the signal waveform. Second, we examine the IFC with signal cooperation, where both the CSI and the signal waveforms are known to transmitters and receivers. Then, for the both scenarios, we identify the Pareto boundary of the achievable rate-energy (R-E) region which characterizes the optimal tradeoff between the information rate and the harvested energy. To this end, the problems for maximizing the information rate are formulated with minimum required harvested energy constraint. To solve these non-convex problems, we introduce parameterization techniques for characterizing the R-E region. As a result, the original problem is separated into two subproblems, for which closed-form solutions are obtained by addressing the line search method. Finally, we provide numerical examples for the Pareto boundary of the R-E region through simulations

Transmit Beamforming Techniques for Wireless Information and Power Transfer in MISO Interference Channels

This paper investigates simultaneous wireless information and power transfer in multiple-input single-output interference channels, and designs transmit beamforming vectors which achieves the optimal tradeoff between the information rate and the harvested energy. To this end, the problem for maximizing the information rate is formulated with minimum required harvested energy constraint. In order to solve this nonconvex problem, we introduce parameterization techniques for characterizing the achievable rate- energy (R-E) region. As a result, the original problem is separated into two subproblems, for which closed- form solutions are obtained by addressing the line search method. Finally, we provide numerical examples for the achievable R-E region through simulations

Transmit Beamforming Optimization for Wireless Information and Power Transfer in MISO Interference Channels with Signal Cooperation

In simultaneous wireless information and power transfer (SWIPT) systems, dedicated energy signals only convey wireless energy, but not information. For this reason, the energy-carring signals in the SWIPT can be pre- determined in advance and is shared among communication nodes. By exploiting this nature, this paper designs the optimal transmit beamforming vectors for the multiple-input single-output SWIPT interference channel with signal cooperation (IFC-SC), where the energy- carrying signal waveforms are known to transmitters and receivers. Specifically, we aim to identify the optimal tradeoff between the information rate and the harvested energy. To this end, an information rate maximization problem is formulated under minimum required harvested energy constraint, which is non-convex in general. To solve the problem, a new parameterization technique is introduced, and we can decouple the original problem into two subproblems, which yields closed-form beamforming solutions by addressing the line search method for the parameter. Simulation results confirms that the proposed optimal IFC-SC beamforming vectors outperform conventional SWIPT IFC systems