Gunes Karabulut Kurt

Practical Full Duplex Physical Layer Network Coding

We propose a practical network code for the wireless two-way relay channel where all nodes communicate in full duplex (FD) mode. The physical layer network coding (PNC) operation is applied with the FD operating nodes, reducing the transmission time to a single time slot, hence doubling the spectral efficiency when compared to classical PNC systems. In our system, binary phase shift keying modulated signals are transmitted over Rayleigh fading channels. We derive the theoretical error rates at the relay and end nodes according to the maximum likelihood detection rule, in case of non-ideal self-interference cancellation. Theoretical results are also verified via simulations.

A novel perceptual feature set for audio emotion recognition

We present a novel system for audio emotion recognition based on the Perceptual Evaluation of Audio Quality (PEAQ) model as described by the standard, ITU-R BS.1387–1 which provides a mathematical model resembling the human auditory system. The introduced feature set performs perceptual analysis in time, spectral and Bark domains thus enabling us to represent the statistics of emotional audio for arousal and valence modes with a small number of features. Unlike the existing systems, the proposed feature set learns statistical characteristic of emotional differences hence does not require data normalization to eliminate speaker or corpus dependency. Recognition performance obtained for the well known VAM and EMO-DB corpora show that the classification accuracy achieved by the proposed feature set outperforms the reported benchmarking results particularly for valence both for natural and acted emotional data.

A High Data Rate Wireless Communication System With Improved Secrecy: Full Duplex Beamforming

We formulate a joint beamforming vector and power optimization problem for multi-antenna full duplex transmission systems and show that simultaneous transmissions of information bearing signals of legitimate nodes can be optimized to act as artificial noise against eavesdroppers. The proposed system improves the overall throughput, while maintaining secrecy and QoS levels within desired signal-to-interference-plus-noise ratio bounds, without additional power, as verified via simulations.

CONDENSE: A Reconfigurable Knowledge Acquisition Architecture for Future 5G IoT

In forthcoming years, the Internet of Things (IoT) will connect billions of smart devices generating and uploading a deluge of data to the cloud. If successfully extracted, the knowledge buried in the data can significantly improve the quality of life and foster economic growth. However, a critical bottleneck for realizing the efficient IoT is the pressure it puts on the existing communication infrastructures, requiring transfer of enormous data volumes. Aiming at addressing this problem, we propose a novel architecture dubbed Condense which integrates the IoT-communication infrastructure into the data analysis. This is achieved via the generic concept of network function computation. Instead of merely transferring data from the IoT sources to the cloud, the communication infrastructure should actively participate in the data analysis by carefully designed en-route processing. We define the Condense architecture, its basic layers, and the interactions among its constituent modules. Furthermore, from the implementation side, we describe how Condense can be integrated into the Third Generation Partnership Project (3GPP) machine type communications (MTCs) architecture, as well as the prospects of making it a practically viable technology in a short time frame, relying on network function virtualization and software-defined networking. Finally, from the theoretical side, we survey the relevant literature on computing atomic functions in both analog and digital domains, as well as on function decomposition over networks, highlighting challenges, insights, and future directions for exploiting these techniques within practical 3GPP MTC architecture.

OFDMA-based network-coded cooperation: design and implementation using software-defined radio nodes

Benefits of network coding towards enhancing communication quality, both in terms of robustness or data transmission rates, make it a significant candidate as a future networking technology. Conventionally, network coding is mostly used in wired infrastructures, where transmission errors between nodes are negligible. Capturing the provided benefits of network coding via straightforward extension from wired networks to wireless networks is not trivial. In addition to the challenges introduced through the wireless channel impairments, we can also capture the spatial diversity gain provided by the broadcast nature of the wireless channels. In this work, we design and implement a network-coded cooperation (NCC) system that operates in real time through the use of software-defined radio (SDR) nodes for the first time in the literature. We specifically target wireless networks. Our system is based on orthogonal frequency division multiple access (OFDMA) that provides a practical means to enable high transmission rates through the use of narrowband subcarriers. The developed testbed is composed of three source nodes, a relay node and two destination nodes. The transmission of the proposed NCC-OFDMA system is completed in two phases; the broadcast and the relaying phases. Multiplexing of source nodes’ signals is achieved through OFDMA technique. In the broadcast phase, an OFDMA signal is transmitted to relay and destination nodes. In the relaying phase, the relay node first detects the OFDMA signal, generates network-coded symbols, and then transmits these symbols to destination nodes. At the end of these two phases, the destination nodes determine the source nodes’ signals by using network decoders. The destination nodes make use of both the uncoded and network-coded symbols, which are received in broadcast and relaying phases, respectively. Destination nodes then perform network decoding. Through real-time bit error rate and error vector magnitude measurements, we show that the NCC-OFDMA system can significantly improve the communication quality and robustness, while enabling data transmission between multiple users, as known from theoretical analyses. Some features of this implemented NCC-OFDMA system have the potential to be included in 5G standards, due to the improved radio resource usage efficiency.

Energy Harvesting From Multiple RF Sources in Wireless Fading Channels

Energy-harvesting technologies are currently under development to provide power for wireless networks and devices. This paper investigates the usage of radio frequency (RF) signals emitted from wireless nodes as sources in energy-harvesting systems. The system we consider consists of multiple RF source nodes, multiple destination nodes, and an energy-harvesting node with a limited-capacity rechargeable battery. We observe that the total received power at the antenna of the harvesting node changes with the number of RF source nodes and the channel conditions. At the same time, the variation of instantaneous received power and the selected modulation type affect the required time for recharging battery. We study statistical models for the battery recharging time in the presence of multiple RF source nodes and focus on the generalized-K channels that include both large-scale and small-scale fading models. Then, we propose a distribution for the battery recharging time that provides a close and analytically tractable expression. We derive the associated fundamental statistical expressions for the battery recharging time in closed form. The simulations and numerical studies are used to verify the theoretical results. The Gamma distribution provides tight approximation to simulation results in fading wireless channel conditions. Additionally, we present battery recharging test results for two sources as a real-life application of energy harvesting with multiple RF sources. Our test results show close fit with the derived distribution equations, supporting theoretical analyses.

A Tutorial on Network Coded Cooperation

Network Coding (NC) can significantly help increase the efficient use of network resources. However, directly applying NC to wireless networks is not an effective design solution. Wireless channels are prone to bit errors due to fading, possibly generating erroneous decisions at the relay nodes while applying NC. Furthermore, the broadcast nature of wireless channels may provide a direct communication link between source and destination nodes. In order to combat fading channel impairments, and also to exploit the inherent spatial diversity provided through the direct link, network coded cooperation (NCC) techniques should be incorporated to the NC systems for wireless networks. This tutorial provides an overview of the state-of-the-art in the NCC systems, combining the powerful tools of NC and cooperative communication, in order to increase data transmission rates and robustness of multiple source wireless networks.

Lognormal Mixture Shadowing

Modeling the variations in the local mean received power, the shadow fading is a relatively understudied effect in the literature. The inaccuracy of the universally accepted lognormal model is shown in many works. However, proposing other statistical distributions, such as gamma, which are not stemmed from the natural underlying physical process, cannot provide sufficient insights. Conceding the physical process of multiple reflections generating the lognormal distribution, in this paper, we propose a generalized mixture model that can address the modeling inaccuracies observed with a single lognormal distribution that may not correctly represent empirical data sets. To show that lognormal mixture model can be used under any shadow fading condition, we prove that an arbitrary probability density function can accurately be represented by a mixture of lognormal random variables (RVs). One of the main issues associated with mixture models is the determination of the mixture components. Here, we propose two solutions. Our first solution is a Dirichlet-process-mixture-based estimation technique that can provide the optimum number of components. Our second solution is an expectation-maximization (EM) algorithm-based technique for a more practical implementation. The proposed model and solution approaches are applied to our empirical data set, where the accuracy of the mixture model is verified by using both confidence-based and error-vector-norm-based techniques. Concluding this paper, we provide outage and cellular coverage probability expressions, where we show that more accurate shadow fading models yield more realistic performance estimates.

Simulation and measurement of spatial correlation in MIMO systems with ray tracing

Multiple-Input-Multiple-Output (MIMO) systems are being used in the majority of communication systems because of the capacity advantages that they provide. The correlation value between signals is a parameter that should be carefully considered while planning multi-antenna systems. In this paper, we emphasize the correlation between antenna elements in a multi-antenna system which has the minimum interelement spacing of 0.02λ. The spatial correlation value is studied with simulation and measurements while the transmission channel is modeled with optical ray-tracing method. Based on our simulation and measurement results, we demonstrate that even when the distance between antennas are larger than λ, high spatial correlation can be obtained between signals in indoor propagation environments, when a few optical ray components are effective.

Electromagnetic Imaging of Closely Spaced Objects Using Matching Pursuit Based Approaches

In this letter, sparse signal recovery framework is applied for the reconstruction of two closely placed point-like objects from measured scattered electromagnetic field. Greedy matching pursuit-based algorithms are investigated as the sparsity promoting method. The performances of the matching pursuit algorithms are compared against convex relaxation methods. Orthogonal matching pursuit algorithm implemented with a flexible tree structure is shown to improve the resolution for the inverse scattering problem.