We focus on a dual-functional multi-input-multioutput (MIMO) radar-communication (RadCom) system, where a single transmitter with multiple antennas communicates with downlink cellular users and detects radar targets simultaneously. Several design criteria are considered for minimizing the downlink multiuser interference. First, we consider both omnidirectional and directional beampattern design problems, where the closedform globally optimal solutions are obtained. Based on the derived waveforms, we further consider weighted optimizations targeting a flexible tradeoff between radar and communications performance and introduce low-complexity algorithms. Moreover, to address the more practical constant modulus waveform design problem, we propose a branch-and-bound algorithm that obtains a globally optimal solution, and derive its worst-case complexity as function of the maximum iteration number. Finally, we assess the effectiveness of the proposed waveform design approaches via numerical results.

Groupware technologies have become an important part of the business computing infrastructure in many organizations, but many groupware applications, especially those requiring significant collaboration and cooperation among users, are still not adequately used. While the successful implementation of groupware depends on many different factors, achieving a 'critical mass' of users has been recognised as the key for groupware acceptance. By extending the technology acceptance model (TAM), this paper advances a groupware acceptance model that incorporates perceived critical mass as an independent variable for predicting groupware acceptance. The model is empirically evaluated using survey data collected from 385 students responding about their perception of Lotus Domino Discussion Databases. The results reveal that perceived critical mass had the largest total effect (direct and indirect) on intention to use groupware. Other relationships postulated in the model were also found to be significant. These findings corroborate the belief that it is essential to create a critical mass of users in the early stages of groupware implementation. A discussion of the implications of these findings for managers and researchers is also presented.

This paper gives the long sought network version of water-filling named as polite water-filling.Unlike in single-user MIMO channels, where no one uses general purpose optimization algorithms in place of the simple and optimal water-filling for transmitter optimization, the traditional water-filling is generally far from optimal in networks as simple as MIMO multiaccess channels (MAC) and broadcast channels (BC), where steepest ascent algorithms have been used except for the sum-rate optimization. This is changed by the polite water-filling that is optimal for all boundary points of the capacity regions of MAC and BC and for all boundary points of a set of achievable regions of a more general class of MIMO B-MAC interference networks, which is a combination of multiple interfering broadcast channels, from the transmitter point of view, and multiaccess channels, from the receiver point of view, including MAC, BC, interference channels, X networks, and most practical wireless networks as special case. It is polite because it strikes an optimal balance between reducing interference to others and maximizing a link's own rate. Employing it, the related optimizations can be vastly simplified by taking advantage of the structure of the problems. Deeply connected to the polite water-filling, the rate duality is extended to the forward and reverse links of the B-MAC networks. As a demonstration, weighted sum-rate maximization algorithms based on polite water-filling and duality with superior performance and low complexity are designed for B-MAC networks and are analyzed for Interference Tree (iTree) Networks, a sub-class of the B-MAC networks that possesses promising properties for further information theoretic study. 5 interpretation.Directly applying single-user water-filling to networks is referred to as selfish water-filling here. It is well known to be far from optimal [26]-[28] because it does not control interference to others. Based on selfish water-filling, game-theoretic, distributed, and iterative algorithms have been well studied for DSL [26], [29]-[33], for MIMO interference channels, e.g., [34]-[37], and for multiaccess channels, e.g., [28]. The algorithms converge only under stringent conditions and the performance is not near optimal.The importance of controlling interference to others has been recognized in literature, e.g., [11],[38]- [40]. But a systematic, general, and optimal method has not been found. In interference pricing method, each user maximizes its own utility minus the interference cost determined by the interference prices. With a proper choice of the interference price which can be reverse engineered from the KKT conditions, the interference pricing based method can find a stationary point of the sum utility maximization problem. Several monotonically convergent interference pricing algorithms have been proposed in [41]-[43] for the SISO/MISO interference channels, and the MIMO interference channel with single data stream transmission. Except for the SISO case, all these algorithms update e...

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The movement toward the increased use of analytics in organizations has generated much discussion by academics and professionals about the impacts and opportunities that analytics offers. Although operations research (OR) has been a driving force in applying quantitative and analytical models for organizational decision making, it is less clear how we as OR practitioners can take advantage of the surging interest in analytics to promote the OR profession and expand its reach. In this paper, we discuss the drivers of the analytics movement, an example of an analytics project, and the opportunities and implications for OR, i.e., the problem scope, models and methods, implementation issues, organizational role, professional skills, and education.