Conference on Information Sciences and Systems 

About: Conference on Information Sciences and Systems is an academic conference. The conference publishes majorly in the area(s): Communication channel & MIMO. Over the lifetime, 2555 publications have been published by the conference receiving 35921 citations.

Compressive sensing

Abstract: This paper overviews the recent work on compressive sensing, a new approach to data acquisition in which analog signals are digitized for processing not via uniform sampling but via measurements using more general, even random, test functions. In stark contrast with conventional wisdom, the new theory asserts that one can combine "low-rate sampling" with digital computational power for efficient and accurate signal acquisition. Compressive sensing systems directly translate analog data into a compressed digital form; all we need to do is "decompress" the measured data through an optimization on a digital computer. The implications of compressive sensing are promising for many applications and enable the design of new kinds of analog-to-digital converters, cameras, and imaging systems.

Multistage detection in asynchronous code-division multiple-access communications

Abstract: A multiuser detection strategy for coherent demodulation in an asynchronous code-division multiple-access system is proposed and analyzed. The resulting detectors process the sufficient statistics by means of a multistage algorithm based on a scheme for annihilating successive multiple-access interference. An efficient real-time implementation of the multistage algorithm with a fixed decoding delay is obtained and shown to require a computational complexity per symbol which is linear in the number of users K. Hence, the multistage detector contrasts with the optimum demodulator, which is based on a dynamic programming algorithm, has a variable decoding delay, and has a software complexity per symbol that is exponential in K. An exact expression is obtained and used to compute the probability of error is obtained for the two-stage detector, showing that the two-stage receiver is particularly well suited for near-far situations, approaching performance of single-user communications as the interfering signals become stronger. The near-far problem is therefore alleviated. Significant performance gains over the conventional receiver are obtained even for relatively high-bandwidth-efficiency situations. >

Information Exchange in Wireless Networks with Network Coding and Physical-layer Broadcast

Abstract: —We show that mutual exchange of independentinformation between two nodes in a wireless network can be effi-ciently performed by exploiting network coding and the physical-layer broadcast property offered by the wireless medium. Theproposed approach improves upon conventional solutions thatseparate the processing of the two unicast sessions, correspondingto information transfer along one direction and the oppositedirection. We propose a distributed scheme that obviates theneed for synchronization and is robust to random packet lossand delay, and so on. The scheme is simple and incurs minoroverhead. I. I NTRODUCTION In this paper, we investigate the mutual exchange of inde-pendent information between two nodes in a wireless network.Let us name the two nodes in consideration a and b, respec-tively. Consider a packet-based communication network withall packets of equal size. The basic problem is very simple: awants to transmit a sequence of packets {X 1 (n)} to b andb wants to transmit a sequence of packets {X

1-Bit compressive sensing

Abstract: Compressive sensing is a new signal acquisition technology with the potential to reduce the number of measurements required to acquire signals that are sparse or compressible in some basis. Rather than uniformly sampling the signal, compressive sensing computes inner products with a randomized dictionary of test functions. The signal is then recovered by a convex optimization that ensures the recovered signal is both consistent with the measurements and sparse. Compressive sensing reconstruction has been shown to be robust to multi-level quantization of the measurements, in which the reconstruction algorithm is modified to recover a sparse signal consistent to the quantization measurements. In this paper we consider the limiting case of 1-bit measurements, which preserve only the sign information of the random measurements. Although it is possible to reconstruct using the classical compressive sensing approach by treating the 1-bit measurements as plusmn 1 measurement values, in this paper we reformulate the problem by treating the 1-bit measurements as sign constraints and further constraining the optimization to recover a signal on the unit sphere. Thus the sparse signal is recovered within a scaling factor. We demonstrate that this approach performs significantly better compared to the classical compressive sensing reconstruction methods, even as the signal becomes less sparse and as the number of measurements increases.

Status updates through queues

Abstract: Anytime, anywhere network connectivity, together with portable sensing and computing devices have led to applications in which sources, for example people or environmental sensors, send updates of their status, for example location, to interested recipients, say a location service. These applications desire status updates at the recipients to be as timely as possible; however, this is typically constrained by limited network resources. We employ a time-averaged age metric for characterizing performance of such status update systems. We use system abstractions consisting of a source, a service facility and monitors, with the model of the service facility (physical constraints) a given. While prior work examined first-come-first-served (FCFS) queues, this paper looks at the queue discipline of last-come-first-served (LCFS). We explore LCFS systems with and without the ability to preempt the packet currently in service. For each we derive a general expression for system age and solve for the average age a Poisson source can achieve given memoryless service. Specifically, when preemption is allowed, we evaluate how the source would share the service facility with other independent Poisson sources.