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Publication Metadata only Joint channel estimation and resource allocation for MIMO systems-part I: Single-user analysis(2010) Soysal, Alkan; Ulukus, Sennur; Soysal, Alkan, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Ulukus, Sennur, Department of Electrical & Computer Engineering, A. James Clark School of Engineering, College Park, United StatesMultiple antenna systems are known to provide very large data rates, when the perfect channel state information (CSI) is available at the receiver. However, this requires the receiver to perform a noise-free, multi-dimensional channel estimation, without using communication resources. In practice, any channel estimation is noisy and uses system resources. We shall examine the trade-off between improving channel estimation and increasing the achievable data rate. We consider transmitside correlated multi-input multi-output (MIMO) channels with block fading, where each block is divided into training and data transmission phases. The receiver has a noisy CSI that it obtains through a channel estimation process, while the transmitter has partial CSI in the form of covariance feedback. In Part I of this two-part paper, we consider the single-user case, and optimize the achievable rate jointly over parameters associated with the training phase and data transmission phase. In particular, we first choose the training signal to minimize the channel estimation error, and then, develop an iterative algorithm to solve for the optimum system resources such as time, power and spatial dimensions. Specifically, the algorithm finds the optimum training duration, the optimum allocation of power between training and data transmission phases, the optimum allocation of power over the antennas during the data transmission phase. © 2010 IEEE. © 2010 Elsevier B.V., All rights reserved.Publication Metadata only Joint channel estimation and resource allocation for MIMO systems-part II: Multi-user and numerical analysis(2010) Soysal, Alkan; Ulukus, Sennur; Soysal, Alkan, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Ulukus, Sennur, Department of Electrical & Computer Engineering, A. James Clark School of Engineering, College Park, United StatesThis is the second part of a two-part paper on the joint channel estimation and resource allocation problem in MIMO systems with noisy channel estimation at the receiver side and partial CSI, in the form of covariance feedback, available at the transmitter side. We consider transmit-side correlated MIMO channels with block fading, where each block is divided into training and data transmission phases. In this paper, we extend the single-user results of Part I to the multiple access channel. For the data transmission phase, we propose an iterative algorithm to solve for the optimum system resources such as time, power and spatial dimensions. This algorithm updates the parameters of the users in a round-robin fashion. In particular, the algorithm updates the training and data transmission parameters of a user, when those of the rest of the users are fixed, in a way to maximize the achievable sum-rate in a multiple access channel, and iterates over users in a round-robin fashion. Finally, we provide a detailed numerical analysis to support the analytical results of both parts of this two-part paper. © 2010 IEEE. © 2010 Elsevier B.V., All rights reserved.Publication Metadata only MIMO systems with non-exact CSI, Eksik kanal bilgisi Altinda MIMO sistemler(2010) Soysal, Alkan; Soysal, Alkan, Bahçeşehir Üniversitesi, Istanbul, TurkeyMultiple antenna systems are known to provide very large data rates, when the perfect channel state information is available at the receiver. However, this requires the receiver to perform a noise-free, multi-dimensional channel estimation, without using communication resources. In practice, any channel estimation is noisy and uses system resources. We shall examine the trade-off between improving channel estimation and increasing the achievable data rate. Lower and upper bounds for the capacity of the system will be derived. ©2010 IEEE. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only Tightness of capacity bounds in correlated MIMO systems with channel estimation error(2010) Soysal, Alkan; Soysal, Alkan, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, TurkeyWe consider a point-to-point, correlated and block fading multiple antenna channel where the receiver has a noisy channel estimation and the transmitter has the statistics of the channel. Although very high rates are promised when the receiver knows the channel perfectly, the capacity is not known when the receiver has a noisy channel estimation. In this paper, we will derive an upper bound to the capacity of the system that we consider, and analyze the tightness of this bound and previously derived lower bounds with respect to block length and total average power. We observe that the lower and upper bounds converge with increasing block length, however there is a non-vanishing difference between the bounds with increasing total average power. ©2010 IEEE. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only A fast power allocation algorithm for MIMO relay channels, MIMO aktarma kanallarinda güç tahsisi i̇çin hizli bir algoritma(2011) Aygün, Bengi; Soysal, Alkan; Aygün, Bengi, Bahçeşehir Üniversitesi, Istanbul, Turkey; Soysal, Alkan, Bahçeşehir Üniversitesi, Istanbul, TurkeyBy assuming full-duplex mode, we consider a MIMO relay channel where the receivers have perfect channel state information (CSI) and the transmitters have partial CSI. Lower bound achieving transmit covariance matrices are derived using an iterative algorithm. Lower bound to the capacity is analyzed for three cases depending on the channel covariance matrix. In the first case, lower bound on the capacity is equal to the capacity of the link from source to relay. In the second case, lower bound on the capacity is equal to the multi access channel capacity from source and relay to the destination. In the last case, lower bound on the capacity depends on both multi access channel and source to relay channel. In that case, under a certain practical channel assumption, we propose a fast power allocation algorithm. © 2011 IEEE. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only Achieving the lower bound of fading MIMO relay channels with covariance feedback at the transmitters(2011) Aygün, Bengi; Soysal, Alkan; Aygün, Bengi, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Soysal, Alkan, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, TurkeyIn this paper, we consider a full-duplex mode MIMO relay channel for decode and forward strategy where the receivers have perfect channel state information (CSI) and the transmitters have only covariance feedback at the transmitters. We derive a lower bound to the ergodic capacity for this scenario and propose an iterative algorithm that finds lower bound achieving transmit covariance matrices of the source and relay nodes. The solution of the optimization problem in the lower bound expression is given for three cases depending on channel covariance matrices. For one of these cases, it seems that an efficient and fast algorithm achieving the lower bound is not possible. However, under a certain practical channel assumption, we propose a power allocation algorithm that gives a solution much faster than classical convex optimization methods. Moreover, we show that this fast algorithm results in a data rate which is very close to the lower bound to the capacity. © 2011 IEEE. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only A method for optimizing matrix valued functions and its applications to capacity of MIMO systems(2011) Soysal, Alkan; Soysal, Alkan, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, TurkeyWe present a method, that is based on differential matrix calculus, for optimizing matrix valued functions. This method can be applied to MIMO capacity optimization problems where a transmit covariance matrix has to be chosen optimally. We first state the necessary mathematical preliminaries regarding matrix differential calculus. Then, we apply the method to some of the already solved MIMO systems. This gives an insight on how the method works. Finally, we apply the method to some unsolved MIMO systems and find their optimum solutions. © 2011 IEEE. © 2012 Elsevier B.V., All rights reserved.Publication Metadata only Capacity bounds on MIMO relay channel with covariance feedback at the transmitters(Institute of Electrical and Electronics Engineers Inc., 2013) Aygün, Bengi; Soysal, Alkan; Aygün, Bengi, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Soysal, Alkan, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, TurkeyIn this paper, the source and relay transmit covariance matrices are jointly optimized for a fading multiple-antenna relay channel when the transmitters only have partial channel state information (CSI) in the form of covariance feedback. For both full-duplex and half-duplex transmissions, we evaluate lower and upper bounds on the ergodic channel capacity. These bounds require a joint optimization over the source and relay transmit covariance matrices. The methods utilized in the previous literature cannot handle this joint optimization over the transmit covariance matrices for the system model considered in this paper. Therefore, we utilize matrix differential calculus and propose iterative algorithms that find the transmit covariance matrices to solve the joint optimization problem. In this method, there is no need to specify first the eigenvectors of the transmit covariance matrices. The algorithm updates both the eigenvectors and the eigenvalues at each iteration. Through simulations, we observe that lower and upper bounds are close to each other. However, the distance between the lower and upper bounds depends on the channel conditions. If the mutual information on the source-to-relay channel and the broadcast channel get closer to each other, the bounds on capacity also get closer. © 1967-2012 IEEE. © 2017 Elsevier B.V., All rights reserved.Publication Metadata only Fading MIMO relay channels with channel estimation error(Institute of Electrical and Electronics Engineers Inc., 2013) Aygün, Bengi; Soysal, Alkan; Aygün, Bengi, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Soysal, Alkan, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, TurkeyIn this paper, we consider a full-duplex, decode-and-forward, fading MIMO relay channel where the transmitters have partial channel state information (CSI) and the receivers have noisy channel estimates. Under block fading assumption, we divide the transmission block into two parts: training phase and data transmission phase. The destination and relay receivers estimate the instantaneous channel realizations during the training phase by using linear minimum mean square error (MMSE) estimation, extract the covariance information of the channel, and feed it back to the source and relay transmitters. We obtain a lower bound expression to the relay channel capacity in terms of a max-min optimization problem over channel estimation and data transmission parameters. By applying matrix differential calculus, we jointly optimize this achievable rate over source and relay transmit covariance matrices, training phase length, training phase powers and training sequences. © 2013 IEEE. © 2016 Elsevier B.V., All rights reserved.Publication Metadata only Short paper: Performance analysis of MIMO-based decode-and-forward relaying VANETs(2013) Aygün, Bengi; Soysal, Alkan; Wyglinski, Alexander M.; Aygün, Bengi, Wireless Innovation Laboratory, School of Engineering, Worcester, United States; Soysal, Alkan, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Wyglinski, Alexander M., Wireless Innovation Laboratory, School of Engineering, Worcester, United StatesIn this paper, we present a novel transceiver architecture for vehicular ad hoc networks (VANETs) employing a combination of decode-and-forward (DF) cooperative communications and multiple-input multiple-output (MIMO) transmission. To assess the performance of the proposed architecture, we have developed a geometric model that is applicable to high mobility environments, where each channel element consists of a sum of complex harmonic exponentials. To assist with the performance assessment, we derived the lower bound on the ergodic channel capacity for the DF scenario. We perform iterative algorithms and provide the transmit covariance matrices which present the certain lower bound for given power constraints. Simulation results show that allocated power over the spatial dimension converge to their optimum value and consequently the exact lower bound is obtained instead of getting sub-optimal achievable rates. © 2013 IEEE. © 2014 Elsevier B.V., All rights reserved.