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—Compressive sensing is a topic that has recently gained much attention in the applied mathematics and signal processing communities. It has been applied in various areas, such as imaging, radar, speech recognition, and data acquisition. In communications, compressive sensing is largely accepted for sparse channel estimation and its variants. In this paper(More)
—In this paper we propose a progressive receiver for orthogonal-frequency-division-multiplexing (OFDM) transmission over time-varying underwater acoustic (UWA) channels. The progressive receiver is in nature an iterative receiver. However, it distinguishes itself from existing iterative receivers in that the system model for channel estimation and data(More)
The buffer cache plays an essential role in smoothing the gap between the upper-level computational components and the lower-level storage devices. A good buffer cache management scheme should be beneficial to not only the computational components, but also to the storage components by reducing disk I/Os. Existing cache replacement algorithms are well(More)
— In this paper we propose a block-by-block iterative receiver for underwater MIMO-OFDM that couples channel estimation with MIMO detection and channel decoding. In particular , the channel estimator is based on a compressive sensing technique to exploit the channel sparsity, the MIMO detector consists of a hybrid use of successive interference cancellation(More)
We present a power-efficient scheme for erasure-coded storage clusters---ECS<sup>2</sup>---which aims to offer high energy efficiency with marginal reliability degradation. ECS<sup>2</sup> utilizes data redundancies and deferred writes to conserve energy. In ECS<sup>2</sup> parity blocks are buffered exclusively in active data nodes whereas parity nodes are(More)