arXiv subjects

Ali Özgür Yılmaz

Publications and source records attributed to Ali Özgür Yılmaz.

11 recordsLinked to original sources

arXiv2025

Downlink Channel Covariance Matrix Estimation via Representation Learning with Graph Regularization

In this paper, we propose an algorithm for downlink (DL) channel covariance matrix (CCM) estimation for frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) communication systems with base station (BS) possessing a uniform linear array (ULA) antenna structure. We consider a setting where the UL CCM is mapped to DL CCM by a mapping function. We first present a theoretical error analysis of learning a nonlinear embedding by constructing a mapping function, which points to the importance of the Lipschitz regularity of the mapping function for achieving high estimation performance. Then, based on the theoretical ground, we propose a representation learning algorithm as a solution for the estimation problem, where Gaussian RBF kernel interpolators are chosen to map UL CCMs to their DL counterparts. The proposed algorithm is based on the optimization of an objective function that fits a regression model between the DL CCM and UL CCM samples in the training dataset and preserves the local geometric structure of the data in the UL CCM space, while explicitly regulating the Lipschitz continuity of the mapping function in light of our theoretical findings. The proposed algorithm surpasses benchmark methods in terms of three error metrics as shown by simulations.

cs.LG↗

arXiv2023

Quasi-Newton FDE in One-Bit Pseudo-Randomly Quantized Massive MIMO-OFDM Systems

This letter offers a new frequency domain equalization (FDE) scheme that can work with a pseudo-random quantization (PRQ) scheme utilizing non-zero threshold quantization in one-bit uplink multi-user massive multiple-input multiple-output (MIMO) systems to mitigate quantization distortion and support high-order modulation schemes. The equalizer is based on Newton's method (NM) and applicable for orthogonal frequency division multiplexing (OFDM) transmission under frequency-selective fading by exploiting the properties of massive MIMO. We develop a low-complexity FDE scheme to obtain a quasi-Newton method. The proposed detector outperforms the benchmark detector with comparable complexity.

cs.IT↗

arXiv2023

Pseudo-Random Quantization Based Two-Stage Detection in One-Bit Massive MIMO Systems

Utilizing low-resolution analog-to-digital converters (ADCs) in uplink massive multiple-input multiple-output (MIMO) systems is a practical solution to decrease power consumption. The performance gap between the low and high-resolution systems is small at low signal-to-noise ratio (SNR) regimes. However, at high SNR and with high modulation orders, the achievable rate saturates after a finite SNR value due to the stochastic resonance (SR) phenomenon. This paper proposes a novel pseudo-random quantization (PRQ) scheme by modifying the quantization thresholds that can help compensate for the effects of SR and makes communication with high-order modulation schemes such as $1024$-QAM in one-bit quantized uplink massive MIMO systems possible. Moreover, modified linear detectors for non-zero threshold quantization are derived, and a two-stage uplink detector for single-carrier (SC) multi-user systems is proposed. The first stage is an iterative method called Boxed Newton Detector (BND) that utilizes Newton's Method to maximize the log-likelihood with box constraints. The second stage, Nearest Codeword Detector (NCD), exploits the first stage solution and creates a small set of most likely candidates based on sign constraints to increase detection performance. The proposed two-stage method with PRQ outperforms the state-of-the-art detectors from the literature with comparable complexity while supporting high-order modulation schemes.

cs.IT↗

arXiv2021

Beamformer Design with Smooth Constraint-Free Approximation in Downlink Cloud Radio Access Networks

It is known that data rates in standard cellular networks are limited due to inter-cell interference. An effective solution of this problem is to use the multi-cell cooperation idea. In Cloud Radio Access Network, which is a candidate solution in 5G and beyond, cooperation is applied by means of central processors (CPs) connected to simple remote radio heads with finite capacity fronthaul links. In this study, we consider a downlink scenario and aim to minimize total power spent by designing beamformers. We consider the case where perfect channel state information is not available in the CP. The original problem includes discontinuous terms with many constraints. We propose a novel method which transforms the problem into a smooth constraint-free form and a solution is found by the gradient descent approach. As a comparison, we consider the optimal method solving an extensive number of convex sub-problems, a known heuristic search algorithm and some sparse solution techniques. Heuristic search methods find a solution by solving a subset of all possible convex sub-problems. Sparse techniques apply some norm approximation ($\ell_0/\ell_1, \ell_0/\ell_2$) or convex approximation to make the objective function more tractable. We also derive a theoretical performance bound in order to observe how far the proposed method performs off the optimal method when running the optimal method is prohibitive due to computational complexity. Detailed simulations show that the performance of the proposed method is close to the optimal one, and it outperforms other methods analyzed.

cs.IT↗

arXiv2021

A Theoretical Performance Bound for Joint Beamformer Design of Wireless Fronthaul and Access Links in Downlink C-RAN

It is known that data rates in standard cellular networks are limited due to inter-cell interference. An effective solution of this problem is to use the multi-cell cooperation idea. In Cloud Radio Access Network (C-RAN), which is a candidate solution in 5G and future communication networks, cooperation is applied by means of central processors (CPs) connected to simple remote radio heads with finite capacity fronthaul links. In this study, we consider a downlink C-RAN with a wireless fronthaul and aim to minimize total power spent by jointly designing beamformers for fronthaul and access links. We consider the case where perfect channel state information is not available in the CP. We first derive a novel theoretical performance bound for the problem defined. Then we propose four algorithms with different complexities to show the tightness of the bound. The first two algorithms apply successive convex optimizations with semi-definite relaxation idea where other two are adapted from well-known beamforming design methods. The detailed simulations under realistic channel conditions show that as the complexity of the algorithm increases, the corresponding performance becomes closer to the bound.

cs.IT↗

arXiv2020

A Reduced Complexity Ungerboeck Receiver for Quantized Wideband Massive SC-MIMO

Employing low resolution analog-to-digital converters in massive multiple-input multiple-output (MIMO) has many advantages in terms of total power consumption, cost and feasibility of such systems. However, such advantages come together with significant challenges in channel estimation and data detection due to the severe quantization noise present. In this study, we propose a novel iterative receiver for quantized uplink single carrier MIMO (SC-MIMO) utilizing an efficient message passing algorithm based on the Bussgang decomposition and Ungerboeck factorization, which avoids the use of a complex whitening filter. A reduced state sequence estimator with bidirectional decision feedback is also derived, achieving remarkable complexity reduction compared to the existing receivers for quantized SC-MIMO in the literature, without any requirement on the sparsity of the transmission channel. Moreover, the linear minimum mean-square-error (LMMSE) channel estimator for SC-MIMO under frequency-selective channel, which do not require any cyclic-prefix overhead, is also derived. We observe that the proposed receiver has significant performance gains with respect to the existing receivers in the literature under imperfect channel state information.

cs.IT↗

arXiv2020

Performance Analysis of Quantized Uplink Massive MIMO-OFDM With Oversampling Under Adjacent Channel Interference

Massive multiple-input multiple-output (MIMO) systems have attracted much attention lately due to the many advantages they provide over single-antenna systems. Owing to the many antennas, low-cost implementation and low power consumption per antenna are desired. To that end, massive MIMO structures with low-resolution analog-to-digital converters (ADC) have been investigated in many studies. However, the effect of a strong interferer in the adjacent band on quantized massive MIMO systems have not been examined yet. In this study, we analyze the performance of uplink massive MIMO with low-resolution ADCs under frequency selective fading with orthogonal frequency division multiplexing in the perfect and imperfect receiver channel state information cases. We derive analytical expressions for the bit error rate and ergodic capacity. We show that the interfering band can be suppressed by increasing the number of antennas or the oversampling rate when a zero-forcing receiver is employed.

cs.IT↗

arXiv2016

Extended OOBE Comparisons for OFDM, GFDM and WCP-COQAM at Equal Spectral Efficiency

Generalized frequency division multiplexing (GFDM), windowed cyclic prefix circular offset quadrature amplitude modulation (WCP-COQAM) and orthogonal frequency division multiplexing (OFDM) are among the candidate 5G modulation formats. In this study, we present additional results for the OOBE comparisons between OFDM, GFDM and WCP-COQAM under equal or unequal spectral efficiency conditions for various simulation scenarios.

cs.IT↗

arXiv2015

Out-of-Band Radiation Comparison of GFDM, WCP-COQAM and OFDM at Equal Spectral Efficiency

GFDM and WCP-COQAM are amongst the candidate physical layer modulation formats to be used in 5G, whose claimed lower out-of-band (OOB) emissions are important with respect to cognitive radio based dynamic spectrum access solutions. In this study, we compare OFDM, GFDM and WCP-COQAM in terms of OOB emissions in a fair manner such that their spectral efficiencies are the same and OOB emission reduction techniques are applied to all of the modulation types. Analytical PSD expressions are also correlated with the simulation based OOB emission results. Maintaining the same spectral efficiency, carrier frequency offset immunities will also be compared.

cs.IT↗

arXiv2015

Pulse Shaping Methods for OQAM/OFDM and WCP-COQAM

GFDM is a new modulation format whose advantages compared to OFDM reportedly make it a preferable modulation format for 5G. However, the non-orthogonal nature of GFDM with matched filtering (MF) receiver for pulses with good time-frequency localization is one of its disadvantages, leading to the proposal of WCP-COQAM, employing offset quadrature amplitude modulation (OQAM). In this paper, we prove that a pulse satisfying orthogonality conditions for OQAM-OFDM will also satisfy orthogonality with WCP-COQAM, thus the pulse design methods developed for OQAM-OFDM can also be used with WCP-COQAM. This statement is also verified by the simulation based results.

cs.IT↗

arXiv2013

Error Rate Analysis of GF(q) Network Coded Detect-and-Forward Wireless Relay Networks Using Equivalent Relay Channel Models

This paper investigates simple means of analyzing the error rate performance of a general q-ary Galois Field network coded detect-and-forward cooperative relay network with known relay error statistics at the destination. Equivalent relay channels are used in obtaining an approximate error rate of the relay network, from which the diversity order is found. Error rate analyses using equivalent relay channel models are shown to be closely matched with simulation results. Using the equivalent relay channels, low complexity receivers are developed whose performances are close to that of the optimal maximum likelihood receiver.

cs.IT↗