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Publication Metadata only Channel estimation and adaptive M-QAM in cognitive radio links(IEEE, 2008) Soysal, Alkan; Ulukus, Sennur; Clancy, Charles; Bahcesehir University; University System of Maryland; University of Maryland College Park; United States Department of DefenseCognitive radios have the ability to sense their RF environment and adapt their transmission parameters to perform optimally in any situation. Part of this involves selecting the best modulation type for a particular channel. In this paper we consider a variable-rate, variable-power, adaptive, M-ary Quadrature Amplitude Modulation (M-QAM) scheme in a single-user communication scenario. The channel between the transmitter and receiver is assumed to be a Rayleigh block-fading channel. Each block is divided into training and data phases. During the training phase, the receiver estimates the channel and feeds the estimate back to the transmitter. During the data phase, the transmitter sends its message by adapting the size of the M-QAM constellation. We first find a closed-form expression that relates the Bit Error Rate (BER) to the constellation size of the M-QAM, and therefore to the data rate of our system. Then, for a given target BER, we maximize the data rate over the training parameters, which are the training signal, the training duration, and the training power. When these optimum parameters are used in a MATLAB implementation, we find that the target BER is matched to within an order of magnitude, and the resulting data rate is close to the theoretical limit.Publication Metadata only MIMO Multiple Access Channels with Noisy Channel Estimation and Partial CSI Feedback(IEEE, 2008) Soysal, Alkan; Ulukus, Sennur; Bahcesehir University; University System of Maryland; University of Maryland College ParkWe consider correlated MIMO multiple access channels with block fading, where each block is divided into training and data transmission phases. We find the channel estimation and data transmission parameters that jointly optimize the achievable data rate of the system. Our results for the training phase are particularly interesting, where we show that the optimum training signals of the users should be non-overlapping in time. For the data transmission phase, we propose an iterative algorithm that 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.Publication Metadata only Joint Channel Estimation and Resource Allocation for MIMO Systems-Part I: Single-User Analysis(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2010) Soysal, Alkan; Ulukus, Sennur; Bahcesehir University; University System of Maryland; University of Maryland College ParkMultiple 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 transmit-side 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.Publication Metadata only Joint Channel Estimation and Resource Allocation for MIMO Systems-Part II: Multi-User and Numerical Analysis(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2010) Soysal, Alkan; Ulukus, Sennur; Bahcesehir University; University System of Maryland; University of Maryland College ParkThis 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.Publication Metadata only Age of Information Scaling in Large Networks with Hierarchical Cooperation(IEEE, 2019) Buyukates, Baturalp; Soysal, Alkan; Ulukus, Sennur; University System of Maryland; University of Maryland College Park; Bahcesehir UniversityGiven n randomly located source-destination (S-D) pairs on a fixed area network that want to communicate with each other, we study the age of information with a particular focus on its scaling as the network size n grows. We propose a three-phase transmission scheme that utilizes hierarchical cooperation between users along with mega update packets and show that an average age scaling of O(n(alpha(h)) log n) per-user is achievable where h denotes the number of hierarchy levels and alpha(h) = 1/3.2(h)+1 which tends to 0 as h increases such that asymptotically average age scaling of the proposed scheme is O(log n). To the best of our knowledge, this is the best average age scaling result in a status update system with multiple S-D pairs.Publication Metadata only Optimality of Beamforming in Fading MIMO Multiple Access Channels(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2009) Soysal, Alkan; Ulukus, Sennur; Bahcesehir University; University System of Maryland; University of Maryland College ParkWe consider the sum capacity of a multi-input multi-output (MIMO) multiple access channel (MAC) where the receiver has the perfect channel state information (CSI), while the transmitters have either no or partial CSI. When the transmitters have partial CSI, it is in the form of either the covariance matrix of the channel or the mean matrix of the channel. For the covariance feedback case, we mainly consider physical models that result in single-sided correlation structures. For the mean feedback case, we consider physical models that result in in-phase received signals. Under these assumptions, we analyze the MIMO-MAC from three different viewpoints. First, we consider a finite-sized system. We show that the optimum transmit directions of each user are the eigenvectors of its own channel covariance and mean feedback matrices, in the covariance and mean feedback models, respectively. Also, we find the conditions under which beamforming is optimal for all users. Second, in the covariance feedback case, we prove that the region where beamforming is optimal for all users gets larger with the addition of new users into the system. In the mean feedback case, we show through simulations that this is not necessarily true. Third, we consider the asymptotic case where the number of users is large. We show that in both no and partial CSI cases, beamforming is asymptotically optimal. In particular, in the case of no CSI, we show that a simple form of beamforming, which may be characterized as an arbitrary antenna selection scheme, achieves the sum capacity. In the case of partial CSI, we show that beamforming in the direction of the strongest eigenvector of the channel feedback matrix achieves the sum capacity. Finally, we generalize our covariance feedback results to double-sided correlation structures in the Appendix.Publication Metadata only Age of Information Scaling in Large Networks(IEEE, 2019) Buyukates, Baturalp; Soysal, Alkan; Ulukus, Sennur; University System of Maryland; University of Maryland College Park; Bahcesehir UniversityWe study age of information in a multiple source-multiple destination setting with a focus on its scaling in large wireless networks. There are n nodes that are randomly paired with each other on a fixed area to form n source-destination (SD) pairs. We propose a three-phase transmission scheme which utilizes local cooperation between the nodes by forming what we call mega update packets to serve multiple S-D pairs at once. We show that under the proposed scheme average age of an S-D pair scales as O(n(1/4) log n) as the number of users, n, in the network grows. To the best of our knowledge, this is the best age scaling result for a multiple source-multiple destination setting.Publication Metadata only Age of Information in Multicast Networks with Multiple Update Streams(IEEE, 2019) Buyukates, Baturalp; Soysal, Alkan; Ulukus, Sennur; Matthews, MB; University System of Maryland; University of Maryland College Park; Bahcesehir UniversityWe consider the age of information in a multicast network where there is a single source node that sends time-sensitive updates to n receiver nodes. Each status update is one of two kinds: type I or type II. To study the age of information experienced by the receiver nodes for both types of updates, we consider two cases: update streams are generated by the source node at-will and update streams arrive exogenously to the source node. We show that using an earliest k(1) and k(2) transmission scheme for type I and type II updates, respectively, the age of information of both update streams at the receiver nodes can be made a constant independent of n. In particular, the source node transmits each type I update packet to the earliest k(1) and each type II update packet to the earliest k(2) of n receiver nodes. We determine the optimum k(1) and k(2) stopping thresholds for arbitrary shifted exponential link delays to individually and jointly minimize the average age of both update streams and characterize the pareto optimal curve for the two ages.Publication Metadata only Age of Information in Two-Hop Multicast Networks(IEEE, 2018) Buyukates, Baturalp; Soysal, Alkan; Ulukus, Sennur; Matthews, MB; University System of Maryland; University of Maryland College Park; Bahcesehir UniversityWe consider the age of information in a two-hop multicast network where there is a single source node sending lime-sensitive updates to n(2) end nodes through 11, middle nodes. In the first hop, the source node sends updates to n middle nodes, and in the second hop each middle node relays the update packets that it receives to n end users that are connected to it. We study the age of information experienced by the end nodes, and in particular, its scaling as a function of n. We show that, using an earliest Is transmission scheme, the age of information at the end nodes can be made a constant independent of n. In particular, the source node transmits each update packet to the earliest k(1) of the n middle nodes, and each middle node that receives the update relays it to the earliest k(2) out of 'n end nodes that are connected to it. We determine the optimum k(1) and k(2) stopping values for arbitrary shifted exponential link delays.Publication Metadata only Age of Information in G/G/1/1 Systems(IEEE, 2019) Soysal, Alkan; Ulukus, Sennur; Matthews, MB; Bahcesehir University; University System of Maryland; University of Maryland College ParkWe consider a single server communication setting where the interarrival times of data updates at the source node and the service times to the destination node are arbitrarily distributed. We consider two service discipline models. In the first model, if a new update arrives when the service is busy, it is blocked, in the second model, a new update preempts the current update in service. For both models, we derive exact expressions for the age of information metric with no restriction on the distributions of interarrival and service times. In addition, we derive upper bounds that are easier to calculate than the exact expressions. In the case with blocking, we also derive a second upper bound by utilizing stochastic ordering if the interarrival and service times have log-concave distribution.
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