An OFDM Signal Identification Method for Wireless Communications Systems

Distinction of OFDM signals from single carrier signals is highly important for adaptive receiver algorithms and signal identification applications. OFDM signals exhibit Gaussian characteristics in time domain and fourth order cumulants of Gaussian distributed signals vanish in contrary to the cumulants of other signals. Thus fourth order cumulants can be utilized for OFDM signal identification. In this paper, first, formulations of the estimates of the fourth order cumulants for OFDM signals are provided. Then it is shown these estimates are affected significantly from the wireless channel impairments, frequency offset, phase offset and sampling mismatch. To overcome these problems, a general chi-square constant false alarm rate Gaussianity test which employs estimates of cumulants and their covariances is adapted to the specific case of wireless OFDM signals. Estimation of the covariance matrix of the fourth order cumulants are greatly simplified peculiar to the OFDM signals. A measurement setup is developed to analyze the performance of the identification method and for comparison purposes. A parametric measurement analysis is provided depending on modulation order, signal to noise ratio, number of symbols, and degree of freedom of the underlying test. The proposed method outperforms statistical tests which are based on fixed thresholds or empirical values, while a priori information requirement and complexity of the proposed method are lower than the coherent identification techniques

Time-Frequency Warped Waveforms

The forthcoming communication systems are advancing towards improved flexibility in various aspects. Improved flexibility is crucial to cater diverse service requirements. This letter proposes a novel waveform design scheme that exploits axis warping to enable peaceful coexistence of different pulse shapes. A warping transform manipulates the lattice samples non-uniformly and provides flexibility to handle the time-frequency occupancy of a signal. The proposed approach enables the utilization of flexible pulse shapes in a quasi-orthogonal manner and increases the spectral efficiency. In addition, the rectangular resource block structure, which assists an efficient resource allocation, is preserved with the warped waveform design as well.Comment: 4 pages, 5 figures; accepted version (The URL for the final version: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8540914&isnumber=8605392

Bio-Inspired Filter Banks for SSVEP-based Brain-Computer Interfaces

Brain-computer interfaces (BCI) have the potential to play a vital role in future healthcare technologies by providing an alternative way of communication and control. More specifically, steady-state visual evoked potential (SSVEP) based BCIs have the advantage of higher accuracy and higher information transfer rate (ITR). In order to fully exploit the capabilities of such devices, it is necessary to understand the features of SSVEP and design the system considering its biological characteristics. This paper introduces bio-inspired filter banks (BIFB) for a novel SSVEP frequency detection method. It is known that SSVEP response to a flickering visual stimulus is frequency selective and gets weaker as the frequency of the stimuli increases. In the proposed approach, the gain and bandwidth of the filters are designed and tuned based on these characteristics while also incorporating harmonic SSVEP responses. This method not only improves the accuracy but also increases the available number of commands by allowing the use of stimuli frequencies elicit weak SSVEP responses. The BIFB method achieved reliable performance when tested on datasets available online and compared with two well-known SSVEP frequency detection methods, power spectral density analysis (PSDA) and canonical correlation analysis (CCA). The results show the potential of bio-inspired design which will be extended to include further SSVEP characteristic (e.g. time-domain waveform) for future SSVEP based BCIs.Comment: 2016 IEEE International Conference on Biomedical and Health Informatics (BHI

IRS-Enabled Beam-Space Channel

The intelligent reflecting surface (IRS) is emphasized as a controlled scattering cluster. To this end, scatterers and traveling paths of multipath components are classified to build a new channel model. Unlike the conventional modeling, where the channels between system units are modeled independently, the new model considers the channel as a whole and decomposes it based on the traveling paths. The model shows clearly how IRS, in the beam-space context, converts the channel from a problem into a design element. After investigating IRS as a scattering cluster, based on a proposed segmentation scheme, the beamforming problem is considered with a focus on first-order reflections. Passive beamforming at IRS is shown to have two tiers; at the scatterer and antenna levels. A segment-activation scheme is proposed to maximize the received signal power, where the number of transmitting antenna elements to be used is given as a function of IRS positioning and beamforming at the receiver. The results show that while using more transmitting antenna elements to get narrower beams is possible, using fewer elements can give better performance, especially for larger IRS at close distances. The developed model also proves useful in addressing emerging issues in massive MIMO communication, namely, stationarity and spherical wavefronts.Comment: This work has been accepted for publication in IEEE Transactions on Wireless Communication

TURKISH PREP SCHOOL EFL STUDENTS’ BELIEFS ABOUT LANGUAGE LEARNING

This study investigates the relationship between Turkish EFL learners’ beliefs about language learning and learner features, such as gender, age, and language proficiency level. The study was conducted at Anadolu University, School of Foreign Languages, with the participation of 242 Turkish prep school EFL students with different levels of English proficiency in the spring semester of the 2018-2019 academic year. The data were collected using Horwitz’s inventory (1987), “Beliefs about Language Learning Inventory” (BALLI). The results of the study showed no significant relationship between the participants’ features, that is, gender, age, and language proficiency level and their beliefs about language learning. However, subtle relationships were discerned between the participants’ features and their beliefs about language learning. Considered in the light of the results of previous studies on the same issue, the results of our study suggest that the interplay between learner beliefs about language learning and learner features is dynamic, complex, and context-specific, which underline the importance of adopting a hands-on approach with individualized attention to the situation and a timely-intervention of students’ misplaced beliefs about language learning. Taking the results of previous studies into account, the results of this study are discussed and pedagogical implications are offered for stakeholders in language learning and teaching. Keywords: Turkish EFL learners, beliefs about language learning

Network-Independent and User-Controlled RIS: An Experimental Perspective

The march towards 6G is accelerating and future wireless network architectures require enhanced performance along with significant coverage especially, to combat impairments on account of the wireless channel. Reconfigurable intelligent surface (RIS) technology is a promising solution, that has recently been considered as a research topic in standards, to help manipulate the channel in favor of users needs. Generally, in experimental RIS systems, the RIS is either connected to the transmitter (Tx) or receiver (Rx) through a physical backhaul link and it is controlled by the network and requires significant computation at the RIS for codebook (CB) designs. In this paper, we propose a practical user-controlled RIS system that is isolated from the network to enhance communication performance and provide coverage to the user based on its location and preference. Furthermore, a low-complexity algorithm is proposed to aid in CB selection for the user, which is performed through the wireless cloud to enable a passive and energy efficient RIS. Extensive experimental test-bed measurements demonstrate the enhanced performance of the proposed system while both results match and validate each other.Comment: Conference, 6 pages, 5 figures, 1 algorith

Enhancing the Performance of Low Priority SUs Using Reserved Channels in CRN

Cognitive radio networks (CRNs) are considered a promising solution for spectrum resources scarcity and efficient channel utilization. In this letter, multi-dimensional analytical Markov model based on reservation channel access scheme and channel aggregation method is proposed to enhance spectrum utilization, capacity of low priority secondary users (SUs) and reducing handoff probability of SUs. Moreover, the proposed method improves the performance of high priority SUs by providing the capability to resume the connection after dropping. The numerical results indicate that the modified reservation access model can enhance the performance of SUs compared to the traditional basic random access model