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In the early twentieth century, American newspapers enjoyed high circulations while presenting readers with diverse and plentiful content. After 1920, radio broadcasting made even more information available for public consumption, giving audience members an abundant range of media choices. During a time of plenty for readers and listeners, companies in the business of media struggled with the opposite problem: scarcity. As the amount of media content proliferated, the practical ability to disseminate it was determined by the access to scarce resources, and this was true for both radio broadcasting and newspaper publishing. In many respects, the history of the American mass media in the early twentieth century might best be told as a tale of two scarcities, one—the electromagnetic spectrum—defined by absolute limits and the other—the newsprint—defined by access to markets for a particular material, the supply of which often fluctuated in availability and price. [ABSTRACT FROM PUBLISHER]

The array redistribution problem occurs in many important applications in parallel computing. In this paper, we consider this problem in a torus network. Tori are preferred to other multidimensional networks (like hypercubes) due to their better scalability (IEE Trans. Parallel Distrib. Syst. 50(10), 1201–1218, []). We present a message combining approach that splits any array redistribution problem in a series of broadcasts where all sources send messages of the same size, thus a balanced traffic load is achieved. Unlike existing array redistribution algorithms, the scheme introduced in this work eliminates the need for data reorganization in the memory of the source and target processors. Moreover, the processing of the scheduled broadcasts is pipelined, thus the total cost of redistribution is reduced. [ABSTRACT FROM AUTHOR]

Recent research has shown that frequency domain pre-equalization (FDPE) can provide broadcast transmissions over multi-input multi-output (MIMO) frequency selective channels, where the multiple receivers need limited processing. In this paper, we consider the combination of FDPE with parallel and successive Tomlinson-Harashima Precoding (THP) and propose two novel FDPE MIMO schemes, which are referred to as FDPE-P-THP and FDPE-S-THP, respectively, based on the minimum mean square error (MMSE) criterion. The ordering algorithm in the FDPE-S-THP scheme is considered and it is shown that the system with even a randomly selected order can perform almost as well as that with the optimal one. This paper further develops an accurate theoretical performance analysis methodology for the proposed FDPE-THP schemes. Numerical results along with analytical results demonstrate the significant performance improvement of our proposed schemes compared to the conventional FDPE MIMO schemes. The channel estimation errors and channel variation effects on the proposed system are also investigated. It is shown that the performance degradation due to channel variation can be efficiently reduced by applying channel prediction. [ABSTRACT FROM AUTHOR]