Now showing 1 - 10 of 93
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    Cross-layer scheduling with infrequent channel and queue measurements
    (01-12-2009)
    Manikandan, C.
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    Rajesh, Sundaresan
    The downlink scheduling problem in multi-queue multi-server systems under channel uncertainty is considered. Two policies that make allocations based on predicted channel states are proposed. The first is an extension of the well-known dynamic backpressure policy to the uncertain channel case. The second is a variant that improves delay performance under light loads. The stability region of the system is characterized and the first policy is argued to be throughput optimal. A recently proposed policy of Kar et al [1] has lesser complexity, but is shown to be throughput suboptimal. Further, simulations demonstrate better delay and backlog properties for both our policies at light loads. © 2009 IEEE.
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    Channel Conditions for the Optimality of Interference Decoding Schemes for K-user Gaussian Interference Channels
    (01-07-2019)
    Chaluvadi, Ragini
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    Madhuri, Bolli
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    The sum capacity of the general K-user Gaussian Interference Channel (GIC) is known only when the channel coefficients are such that treating interference as noise (TIN) is optimal. The Han-Kobayashi (HK) scheme achieves the best known achievable rate region for the K-user interference channel (IC). Simple HK schemes are HK schemes with Gaussian signaling, no time sharing, and no private-common power splitting. The class of simple HK (S-HK) schemes includes the TIN scheme and schemes that involve various levels of interference decoding and cancellation at each receiver. We derive conditions under which simple HK schemes achieve sum capacity for general K-user Gaussian ICs. These results generalize existing sum capacity results for the TIN scheme to the class of simple HK schemes.
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    Optimal MTM spectral estimation based detection for cognitive radio in HDTV
    (15-05-2012)
    Jataprolu, Manjunath Kashyap
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    Cognitive radio based systems rely on spectrum sensing techniques to detect whitespaces to exploit. For the sake of ease of implementation, simple schemes such as energy detector have been proposed and studied widely. However, such simple schemes perform far from optimally, thereby affecting the performance of the underlying system. On the other hand sophisticated detectors are difficult to implement, giving rise to a trade-off. This paper explores the idea of using spectral estimates for detection. The case of HDTV based cognitive radio is explored and an optimal detection scheme following multi taper estimation is proposed and studied. © 2012 IEEE.
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    Change detection with unknown post-change parameter using Kiefer-Wolfowitz method
    (16-06-2017)
    Singamasetty, Vijay
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    Nair, Navneeth
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    Pachai Kannu, Arun
    We consider a change detection problem with an unknown post-change parameter. The optimal algorithm in minimizing worst case detection delay subject to a constraint on average run length, referred as parallel CUSUM, is computationally expensive. We propose a low complexity algorithm based on parameter estimation using Kiefer-Wolfowitz (KW) method with CUSUM based change detection. We also consider a variant of KW method where the tuning sequences of KW method are reset periodically. We study the performance under the Gaussian mean change model. Our results show that reset KW-CUSUM performs close to the parallel CUSUM in terms of worst case delay versus average run length. Non-reset KW-CUSUM algorithm has smaller probability of false alarm compared to the existing algorithms, when run over a finite duration.
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    Cross-layer strategies for throughput maximization in a data aggregating wireless network
    (01-01-2013)
    Mangipudi, Easwar Vivek
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    We consider an ad hoc wireless network where all nodes have data to send to a single destination node called the sink. We consider a linear placement of the wireless nodes with the sink at one end. We assume that the wireless nodes transfer data to the sink using single hop direct transmission and that the nodes are scheduled one at a time by a central scheduler (possibly the sink). In this setup, we assume that the wireless nodes are power limited and our network objective (notion of fairness) is to maximize the minimum throughput of a node subject to the individual node power constraints. In this work, we consider network designs that permit different node transmission time, node transmission power and node placements, and study cross-layer strategies that seek to maximize the minimum node throughput. Using simulations, we characterize the performance of the different strategies and comment on their applicability for various network scenarios. © 2013 IEEE.
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    On the capacity of the half-duplex MIMO Gaussian diamond channel
    (02-02-2017)
    Mampilly, Antony V.
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    In this paper, we analyze the 2-relay multiple-input multiple-output (MIMO) Gaussian diamond channel. We show that a multihopping decode-and-forward with multiple access (MDF-MAC) protocol achieves rates within a constant gap from capacity when a channel parameter Δ is greater than zero. We also identify the transmit covariance matrices to be used by each relay in the multiple-access (MAC) state of the MDF-MAC protocol. As done for the single-antenna 2-relay Gaussian diamond channel, the channel parameter Δ is defined to be the difference between the product of the capacities of the links from the source to the two relays and the product of the capacities of the links from the two relays to the destination.
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    Optimal multi-antenna transmission with multiple power constraints
    (01-07-2019)
    Chaluvadi, Ragini
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    Nair, Silpa S.
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    We determine the capacity-optimal transmission strategy for a multiple-input-multiple-output (MIMO) Gaussian channel under multiple power constraints, namely joint sum power constraint (SPC), per group power constraints (PGPC), and per antenna power constraints (PAPC). First, we focus on cases where we can analytically determine the optimal transmit strategy under joint SPC-PGPC-PAPC. We obtain results for the following cases: 1) nt × 1 multiple-input-single-output (MISO); 2) MIMO channel with full column rank and full rank optimal covariance matrix; and 3) 2 × nr MIMO channel. These results generalize some recent results for the special cases of PAPC only and joint SPC-PAPC. Then, we propose a projected factored gradient descent (PFGD) algorithm for the general MIMO Gaussian channel under joint SPC-PGPC-PAPC including the possibility of additional rank constraints. This algorithm matches the solution of standard convex optimization tools with lower complexity. The algorithm also overcomes the limitations of existing algorithms, in terms of accuracy and applicability to low rank channels.
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    Eigen-beamforming with delayed feedback and channel prediction
    (19-11-2009)
    Ramya, T. R.
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    Adaptive transmit beamforming based on channel state information (CSI) is a key feature in next generation wireless cellular systems. However, CSI available for adaptation is imperfect due to feedback delay and estimation errors. In this work, we analyze the outage performance of maximum eigen-mode beamforming with imperfect CSI. First we analyze the outage probability in terms of the correlation coefficient ρ between the CSI available at the transmitter (CSIT) and the CSI available at the receiver (CSIR). The analysis shows that feedback delay leads to significant degradation at medium and high signal-to-noise ratios (SNR). Furthermore, the effect of delay can be overcome only if ρ tends to one with increasing SNR. Then, we study whether linear minimum mean squared error (MMSE) prediction can achieve the required behavior in ρ. The length of the prediction filter required is numerically evaluated and shown to increase with SNR. Finally, the asymptotic diversity order is analyzed as a function of the rate at which 1 - ρ approaches 0 as the SNR → ∞. Results show that for 1 - ρ proportional to SNR -1, the asymptotic diversity order remains unaltered. © 2009 IEEE.
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    An asymptotically optimal push-pull method for multicasting over a random network
    (29-07-2013)
    Swamy, Vasuki Narasimha
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    Sundaresan, Rajesh
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    Viswanath, Pramod
    We consider all-cast and multicast flow problems where either all of the nodes or only a subset of the nodes may be in session. Traffic from each node in the session has to be sent to every other node in the session. If the session does not consist of all the nodes, the remaining nodes act as relays. The nodes are connected by undirected links whose capacities are independent and identically distributed random variables. We study the asymptotics of the capacity region (with network coding) in the limit of a large number of nodes, and show that the normalized sum rate converges to a constant almost surely. We then provide a decentralized push-pull algorithm that asymptotically achieves this normalized sum rate without network coding. © 1963-2012 IEEE.
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    Sequential Nonparametric K-Medoid Clustering of Data Streams
    (01-01-2022)
    Sreenivasan, Sreeram C.
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    We study a sequential nonparametric clustering problem to group a finite set of S data streams into K clusters. The data streams are real-valued i.i.d data sequences generated from unknown continuous distributions. The distributions them-selves are organized into clusters according to their proximity to each other based on a certain distance metric. We propose a universal sequential nonparametric clustering test for the case when K is known. We show that the proposed test stops in finite time almost surely and is universally exponentially consistent. We also bound the asymptotic growth rate of the expected stopping time as probability of error goes to zero. Our results generalize earlier work on sequential nonparametric anomaly detection to the more general sequential nonparametric clustering problem, thereby providing a new test for case of anomaly detection where the anomalous data streams can follow distinct probability distributions. Simulations show that our proposed sequential clustering test outperforms the corresponding fixed sample size test.