Communication Complexity of Discrete Fair Division

Communication Complexity of Cake Cutting

We study classic cake-cutting problems, but in discrete models rather than using infiniteprecision real values, specifically, focusing on their communication complexity. Using general discrete simulations of classical infinite-precision protocols (Robertson-Webb and movingknife), we roughly partition the various fair-allocation problems into 3 classes: “easy” (constant number of rounds of logar...

Sampling Rate Conversion in the Discrete Linear Canonical Transform Domain

Sampling rate conversion (SRC) is one of important issues in modern sampling theory. It can be realized by up-sampling, filtering, and down-sampling operations, which need large complexity. Although some efficient algorithms have been presented to do the sampling rate conversion, they all need to compute the N-point original signal to obtain the up-sampling or the down-sampling signal in the tim...

Looking Beyond FDA Warning Letters to Explore Unforeseen Trouble Spots in eDTCA: A Response to Recent Commentaries

Moving Knife Algorithms A Comparison between Discrete and Exact Solutions

Fair division algorithms, especially the ones that require continuous observation, tend to assume synchronicity in decision making and knife movements in theory. However, in practice, it is not always possible to give an exact solution to a fair division algorithm without making some assumptions or error bounds. As such, we would like implement both an exact and discrete solution to given algor...

A Low Complexity Forward Error Correction for PAPR reduction in OFDM Systems

In this paper, a Peak to Average Power Ratio (PAPR) reduction technique in Orthogonal Frequency Division Multiplexing (OFDM) systems is proposed. This technique uses error correction capability of channel coding to reduce the PAPR.The coded bits at the input of OFDM modulator are separated into two groups of the Most Significant Bits (MSB) and the LeastSignificant Bits (LSB). The bits are mappe...