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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 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.Publication Metadata only Energy and Spectral Efficiency for Heterogeneous Cellular Networks with Stochastic Deployment(IEEE, 2017) Demirtas, Mahmut; Saginda, Cagatay; Soysal, Alkan; Bahcesehir UniversityIn this paper, we investigate the energy efficiency and spectral efficiency of heterogeneous networks, where macro cell and microcell base stations are deployed according to two separate stochastic geometry based processes. Here, micro base stations are placed over the regions for which the received signal strength is below a certain limit. By employing the deployment model we propose, we investigate the effects of certain parameters like macro and micro base station densities, and user density on energy efficiency of heterogeneous networks. The results show that deploying micro base stations considerably improves both energy efficiency and spectral efficiency in a dense user scenario.Publication Metadata only Fading MIMO Relay Channels with Channel Estimation Error(IEEE, 2013) Aygun, Bengi; Soysal, Alkan; Bahcesehir UniversityIn 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.Publication Metadata only Fading MIMO Relay Channels with Covariance Feedback(IEEE, 2012) Aygun, Bengi; Soysal, Alkan; Bahcesehir UniversityIn 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 full-duplex transmission, 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 fail to find fast and efficient algorithms for the system model considered in this paper. Therefore, we utilize matrix differential calculus in order to solve the joint optimization problem. In this method, there is no need to specify the eigenvectors of the transmit covariance matrices first. Through simulations, we observe that lower and upper bounds are close to each other.Publication Metadata only Tightness of Capacity Bounds in Correlated MIMO Systems with Channel Estimation Error(IEEE, 2010) Soysal, Alkan; Bahcesehir UniversityWe 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.Publication Metadata only Optimality of Beamforming in Fading MIMO with Noisy Channel Estimation(IEEE, 2014) Soysal, Alkan; Bahcesehir UniversityIn this paper, we consider a single user block fading communication system where both the transmitter and receiver have multiple antennas. A transmission block is divided into training and data transmission phases. The channel estimation at the receiver is noisy. The transmitter has long term statistics of the estimated channel in the form of a covariance matrix. The general problem is to find optimum transmit covariance matrix under these channel state information (CSI) assumptions. Beamforming strategy is optimum when the optimum transmit covariance matrix is unit rank. Previous works find conditions under which beamforming is optimal when the receiver has instantaneous and full CSI. Here, we consider noisy CSI at the receiver and introduce a condition over channel covariance matrix, block length and the transmit power constraint, where beamforming is always the optimum transmission strategy. We show through simulations that beamforming is optimal for a larger set of parameters when block duration is short and when SNR is low. An interesting result we observe through simulations is that beamforming is always optimal when transmission block is at most three symbols long. This means that when block fading becomes faster, beamforming becomes optimal almost always regardless of number of antennas or other parameters.