A rate splitting algorithm is presented for a multiple video transmission system to transfer the aggregation (or statical multiplexing) of multiple video streams to multiple clients so that each client can receive the requested video stream with the reliable fidelity. Computer simulations for transmission of a set of 128 MPEG compressed video streams show that the proposed algorithm alleviates the variability of the aggregate video transmission comparing with a scheme to smooth individually each of videos using the traditional online smoothing algorithm. Besides, the proposed is 2 time faster than the traditional one.

We consider coding for sources that output the symbols according to Poisson process from the viewpoint of real-time transmission. In order to reduce the transmission delay we avoid using input buffers. However, the lack of buffer causes overflow error. The theoretical relation between the transmission rate and the error probability is clarified. It is shown that the optimal code that minimizes the probability of error differs from the code that minimizes the expected codeword length. We also investigate the case of block coding as one of the applications of buffers.

Sudoku is a pencil puzzle. The aim of the solver is to complete the 9×9 grid by filling in a digit in every cell according to a certain rule. In this study, we regard the process of solving Sudoku as a process of decoding a codeword from a received word, and show the expected decoding error probability for erasure channels obtained by experiments.

An improved arithmetic coding which provides an encoder with finite calculation precision for source sequences over a countable alphabet is presented. Conventional arithmetic coding theoretically has infinite precision for real variables. However any algorithm implemented on a computer has finite precision. This implies that conventional arithmetic codes can only encode sequences over a finite alphabet. The improved arithmetic coding presented here has a computational complexity which is roughly proportional to the length of the source sequence for a given source.

In this paper, we propose a protocol for multicast communication called Multicast Datagram Transfer Protocol (MDTP) to provide multicast for video broadcasting service on the Internet. MDTP is a one-to-many multicast communication protocol, which is constructed based on IPv4 unicast protocol by utilizing IP Router Alert Option, and it uses unicast addressing and unicast routing protocol. A mechanism is presented to allow a router to remove identical video stream, to duplicate a video stream, and to forward each copy of the duplicated video stream to its destinations. Ordinary IP routers that do not support MDTP will treat the MDTP packets as normal unicast packets. Hence, gradual deployment is possible without tunneling technique. With a delegation mechanism, MDTP router is also able to handle request from clients, and serve the requested video stream. The simulation results show that the average bandwidth usage of MDTP is close to the average bandwidth usage of IP multicast. MDTP also has greater efficiency than XCAST, and its efficiency becomes significant for a large number of clients.

In the source coding problem with cost constraint, a cost function is defined over the code alphabet. This can be regarded as a noiseless channel coding problem with cost constraint. In this case, we will not distinguish between the input alphabet and the output alphabet of the channel. However, we must distinguish them for a noisy channel. In the channel coding problem with cost constraint so far, the cost function is defined over the input alphabet of the noisy channel. In this paper, we define the cost function over the output alphabet of the channel. And, the cost is paid only after the received word is observed. Note that the cost is a random variable even if the codeword is fixed. We show the channel capacity with cost constraint defined over the output alphabet. Moreover, we generalize it to tolerate some decoding error and some cost overrun. Finally, we show that the cost constraint can be described on a subset of arbitrary set which may have no structure.

The achievability part of the rate-distortion theorem is proved by showing existence of good codes. For i.i.d. sources, two methods showing existence are known; random coding and non-random coding. For general sources, however, no proof in which good codes are constructed with non-random coding is found. In this paper, with a non-random method of code construction, we prove the achievability part of the rate-distortion theorem for general sources. Moreover, we also prove a stochastic variation of the rate-distortion theorem with the same method.

A channel coding problem with cost constraint for general channels is considered. Verdú and Han derived ϵ-capacity for general channels. Following the same lines of its proof, we can also derive ϵ-capacity with cost constraint. In this paper, we derive a formula for ϵ-capacity with cost constraint allowing overrun. In order to prove this theorem, a new variation of Feinstein's lemma is applied to select codewords satisfying cost constraint and codewords not satisfying cost constraint.