Yazar "Mutlu, Ural" seçeneğine göre listele

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    Approximate Error Probability Analysis of L-Branch MRC System over ?-? Fading Environments
    (IEEE, 2024) Mutlu, Ural; Bilim, Mehmet; Kabalci, Yasin
    The increase in research conducted on next-generation communication systems has directed research interest toward new modulation schemes, channel models, and diversity techniques that promise enhanced efficiency. Recently, new analytical channel models capable of better modeling the wireless communication environment have been developed. In this study, the approximate error performance of hexagonal quadrature amplitude modulation (HQAM) in lambda - mu fading channels for multi-branch single-input multiple-output (SIMO) systems is investigated. An analytical expression for the error probability of the considered system is derived using the Prony approximation for the Gaussian Q function. Subsequently, an error probability expression for the considered system is proposed. Comparative results between the approximate results obtained from the derived expression and the exact simulation results are presented. Different scenarios are evaluated to analyze the effects of channel fading parameters, the number of transmission branches, and modulation levels, resulting in numerical outcomes. Ultimately, it was observed that the approximate results obtained from the proposed expression closely matched the exact simulation results, confirming the accuracy of the proposed analytical expression.
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    Array gain analyses of MIMO systems in 5G communication systems
    (2022) Mutlu, Ural; Kabalcı, Yasin
    In the last decade, Multiple-Input Multiple-Output (MIMO) algorithms have been developed for mobile communication networks in order to increase spectrum efficiency and reduce transmitted power, which are also two of the main Key Performance Indicators of Fifth Generation New Radio (5G NR). Therefore, various MIMO algorithms are being researched for their adaptability to 5G NR specifications. The objective of this study is to examine the array gains achieved with the deployment of multiple transmit antennas and multiple receive antennas in 5G NR Physical Downlink Shared Channel (PDSCH). The study first examines the array gains of Single-Input Multiple-Output (SIMO) and Multiple-Input Single-Output (MISO), then combines the transmitter and the receiver diversities in a MIMO system for 5G PDSCH. The array gains are achieved through precoding and combining vectors obtained by Singular Value Decomposition (SVD) of the channel coefficients matrix. The results show that theoretical array gains can be achieved in end-to-end 5G NR downlink channels.
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    Channel Estimation In Intelligent Reflecting Surfaces for 5G and Beyond
    (IEEE, 2022) Mutlu, Ural; Kabalci, Yasin
    Intelligent Reflecting Surfaces (IRS) are constructed of multiple independently controllable passive Reflecting Elements (RE), which can change the phase and amplitude of the reflected signals so that the reflected signals can be combined in coherent manner to achieve beamforming. To facilitate beamforming, the channel coefficients of the incoming and outgoing channels need to be estimated. In this study, the Discrete Fourier Transform (DFT) based channel estimation method is applied to an IRS-assisted communication system implementing Fifth Generation (5G) Orthogonal Frequency Division Multiplexing (OFDM) waveform in order to observe the effectiveness of the estimation method. DFT-based channel estimation has the advantage of not using the whole OFDM symbol for pilot transmission, thus it can be performed while transmitting data. Therefore, the effects of multipath delay spread, the number of REs, and training sequence sparsity in the OFDM symbol are observed for different Signal-to-Noise Ratio (SNR) values with a direct path and without a direct path. The results show that delay spread has a significant effect on the performance and training sequence length can be reduced.
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    Channel Estimation in RIS-aided Multi-User OFDM Communication Systems
    (IEEE, 2024) Mutlu, Ural; Kabalci, Yasin; Cengiz, Alperen
    Reconfigurable Intelligent Surfaces (RIS) are planar arrays constructed of independently controllable passive reflecting elements that change the phase and the amplitude of the reflected signals between Base Station (BS) and User Equipment (UE). To facilitate the coherent combination of the reflected signals, the Channel State Information (CSI) of the channels should be known by the communication network. The main issue with CSI estimation in unstructured channels is the high number of channels and the long training time that is required to apply orthogonal training reflection patterns at the RIS. With multiple users, the required training period becomes even longer. Therefore, this study proposes allocating the users with orthogonal pilot sequences, which are transmitted over the orthogonal frequency division multiplexing (OFDM) frequency domain with the aim of separating the user signals in the frequency domain. In the study, the cascaded channels are separated in the time domain by a reflection pattern consisting of a DFT matrix and the users are separated in the frequency domain by the use of the Hadamard matrix. The algorithms are simulated over a 3GPP-defined Tapped Delay Line (TDL) channel model as well as a Rayleigh fading channel. The results show that due to the use of orthogonal sequences, channel estimation improves in flat fading channels, while the performance is also of acceptable level in frequency selective channels.
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    Deep Learning Aided Channel Estimation Approach for 5G Communication Systems
    (IEEE, 2022) Mutlu, Ural; Kabalci, Yasin
    The defining feature of the Fifth Generation (5G) mobile communication systems is going to be Multiple Input Multiple Output (MIMO) transmission scheme, which utilizes the multipath diversities to achieve beamforming and increase spectral efficiency. However, these MIMO algorithms rely on accurate channel parameters. To improve the accuracy of the channel coefficients, the study presents a Deep Learning (DL) based approach that uses the 5G Demodulation Reference Signals (DMRS) as training sequence and Deep Neural Networks (DNN) as training and prediction network in a MIMO scenario. The DNN is trained with training data obtained by applying Least Squares (LS) method to the received pilot signals and by comparing it to Clustered Delay Line (CDL) channel model. The DNN is then used to predict real-time channel coefficients. The results show that the model improves channel estimation performance by reducing the effects of noise, thus improving the Normalized Mean Square Error (NMSE) versus Signal-to-Noise Ratio (SNR) metric of the MIMO system.
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    Deep Learning Aided Channel Estimation in Intelligent Reflecting Surfaces
    (IEEE, 2023) Mutlu, Ural; Kabalci, Yasin
    Intelligent Reflecting Surfaces (IRS) consist of multiple independently controllable passive reflecting elements that can change the phase and the amplitude of the reflected signals to achieve passive beamforming. To facilitate passive beamforming, channel state information (CSI) needs to be available at the Base Station so that the optimum reflection pattern can be calculated. Therefore, the objective of this research is to present a Deep Learning (DL) based approach to improve the accuracy of the channel estimation in an IRS aided Multiple Input Single Output - Orthogonal Frequency Division Multiplexing (MISO-OFDM) wireless network. A Convolutional Neural Network (CNN) that treats OFDM frames as images is adapted for IRS and applied to the direct and cascaded channels. The CNN presented in the study is trained with channel coefficients obtained by Least Squares (LS) method and Discrete Fourier Transform (DFT) as the reflection pattern at the IRS. The results show that the CNN improves channel estimation efficiency by reducing the effects of noise and improving the Normalized Mean Square Error (NMSE) parameters.
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    Emerging Communication Technologies for V2X: Standards and Protocols
    (Springer Science and Business Media Deutschland GmbH, 2023) Kabalci, Yasin; Mutlu, Ural
    The objective of the early Intelligent Transportation Systems (ITS) was to improve road and traffic safety and to facilitate the management of the transportation system by providing Vehicle-to-Everything (V2X) communications to the vehicles and the entities surrounding it. With the recent advances in V2X technologies and the increasing popularity of Electric Vehicles (EVs), the EVs are envisaged to become part of the ITS. Moreover, V2X communications enable the integration of the EVs as interconnected entities into the Smart Grid ecosystem. Thus, the Smart Grid can perform enhanced monitoring and control capabilities by collecting data not only from the vehicle but also from the overall road infrastructure. Therefore, this chapter presents the V2X communication standards and protocols enabling the EVs to interact wirelessly with the grid infrastructure and other Road Side Units (RSUs). First, the existing Dedicated Short Range Communications (DSRCs), European Telecommunications Standards Institute (ETSI) ITS, and Long-Term Evolution (LTE) Cellular V2X (C-V2X) wireless protocol stacks and requirements, as well as the protocols used in the Vehicle-to-Grid (V2G) communications are outlined. Next, the emerging V2X wireless communication technologies of IEEE 802.11bd and New Radio (NR) V2X designed to provide high reliability, low latency, and high throughput communications to the new generation of autonomous vehicles and autonomous driving use cases are presented in detail. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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    Investigation of Polar Codes in Fifth Generation New Radio Control Channels
    (IEEE, 2021) Mutlu, Ural; Kabalci, Yasin
    The key design principle for the control channels is robustness, as the information within the control channels defines how the physical data channels are established and used. Fifth Generation New Radio (5G NR) Physical Downlink Control Channel (PDCCH) achieves this robustness with the Polar Codes. The objective of this study is to investigate the Polar Codes in PDCCH and simulate their effectiveness as a channel coding scheme in various channel scenarios. First, PDCCH channel coding and decoding is discussed, then mapping of the encoded data on the physical resources is given. The Bit Error Rate (BER) performance of the PDCCH Polar Codes is simulated and evaluated in various Tapped Delay Line (TDL) multipath channel scenarios. The results show that Downlink Control Information (DCI) is successfully decoded and robustness is achieved.
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    Joint Channel Estimation and Localization in RIS Assisted OFDM-MIMO System
    (IEEE, 2024) Mutlu, Ural; Bilim, Mehmet; Kabalci, Yasin
    Reconfigurable Intelligent Surfaces (RISs) are expected to become one of the enabling technologies in the development of the sixth generation (6G) smart radio environment, where services such as localization and sensing are going to be ubiquitous and an integral part of the system. However, achieving localization in a dense urban environment is a challenging task. Therefore, this study considers joint channel and localization estimation in a RIS-assisted orthogonal frequency division multiplexing multiple-input multiple-output (OFDM-MIMO) system operating in a dense urban environment, where only Non-Line-of-Sight (NLoS) multipath components are available. The channel estimation is based on the channels being sparse in the spatial and angular domains and having only a few Angles of Arrival (AoA) and Angles of Departure (AoD), thus the channel estimation becomes a sparse signal recovery problem that can be solved with compressive sensing algorithms. The study implements Simultaneous Orthogonal Matching Pursuit (SOMP) to obtain AoA and AoD. The time delay parameters are obtained by correlating OFDM subcarriers with a search matrix. A localization estimation algorithm based on linearization of the estimated geometric parameters is adopted. The results of the study show that for a channel consisting of 3 NLoS paths, location estimation in the range of decimeters is possible.
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    Outage Probability Analysis of RIS-Assisted System over Weibull/Rayleigh Fading Channels
    (IEEE, 2024) Mutlu, Ural; Bilim, Mehmet; Kabalci, Yasin
    In upcoming communication systems, particularly beyond fifth-generation (B5G) and sixth-generation (6G), reconfigurable intelligent surfaces (RIS) are anticipated to offer significant advancements. This study analyzes the outage probability of an RIS-aided communication system under Weibull and Rayleigh fading conditions. The proposed system model assumes Weibull fading for the channel between the source and RIS, while Rayleigh fading is assumed for the channel between RIS and destination. Numerical simulations are conducted across various configurations to assess the impact of different fading parameters, reflective surface elements, signal-to-noise ratio (SNR), and instantaneous SNR threshold values. Comparative analysis between the results obtained from the derived expression and exact results is presented. Notably, the analytical and simulation results exhibit strong consistency, indicating the robustness of the proposed approach.
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    Performance Analyses of Hybrid-ARQ in Fifth Generation New Radio
    (IEEE, 2021) Mutlu, Ural; Kabalci, Yasin
    The main design criteria of the Fifth-generation (5G) New Radio (NR) specifications are to improve the requirements that enable high-speed, high-reliability, and low-latency communications. To achieve these design requirements, 5G NR specifications have defined the use of Low Density Parity Check (LDPC) codes channel coding scheme for data channels. LDPC codes have been chosen specifically because of their support for wide range of block sizes and code rates as well as their compatibility with Hybrid Automatic Repeat Request (HARQ) protocol. HARQ combines ARQ retransmission scheme with LDPC Forward Error Correction (FEC). In HARQ, a retransmitted code block consists of a different set of parity bits belonging to the same transport block and soft combining of previous copy and retransmitted copy is performed at the receiver. The new set of parity bits effectively reduces the coding rate for the FEC and achieve higher reliability. The objective of this research is to analyse the block error rate (BLER) and throughput performance of the HARQ protocol in 5G NR. The study, first, introduces LDPC codes and explains how LDPC rate matching is combined with HARQ protocol to improve performance. Then, BLER and throughput simulation results for various coding rates and transport block sizes in Tapped Delayed Line (TDL) channel models are presented. The results show that incremental redundancy combining in HARQ improves throughput, reliability, and latency.