Chikato Fujiwara

Exact analysis of bit error probability for 4-state soft decision Viterbi decoding

Although Viterbi decoding is widely used in practical systems, only a few studies have been made for the exact error performance. We already proposed analytical technique for a 2-state soft decision Viterbi decoding. In this paper, this technique is extended to bit error probability for 4-state soft decision Viterbi decoding. This employs an iterative calculation of probability density function (PDF) of the path metrics.

Effective bit selection methods for improving performance of packet classifications on IP routers

In recent years, high-performance routers are needed as well as increasing the link capacity to keep up with the Internet traffic explosion. Routers are preferable to store statistics of the incoming/outgoing traffic to realize the intelligent or policy-based services in the Internet. In this paper, we propose a new packet classification solution, which uses the combination of CAM and DRAM memories. Unlike other algorithms, we do not search the classifier by selecting the front bits, but select bits arbitrary from the classifier as the search key in the CAM. For this purpose, we propose new bit selection methods. Through simulation results, we show that our bit selection methods can decrease the delay of classification.

Topology-aware server selection method for dynamic parallel downloading

For distributed file transfers, parallel downloading is one of effective schemes to shorten a transmission time and/or to get more file transfer rate. In parallel downloading, single file is transferred by using multiple connections to different file servers. However, the effectiveness of parallel downloading is strongly dependent on the physical network topology, i.e., if some connections share the same bottleneck link, the throughput is not increased and the additional connection simply wastes the server resources. In this paper, we propose a server selection method for parallel downloading by taking the physical network topology into consideration. Our approach tries to minimize the total number of shared links between a client and downloading servers. Through simulation results, we show that our method can keep high throughput regardless the network topology and decrease the number of selected servers compared with random server selection.

Performance Improvement on Probabilistic Packet Marking by using History Caching

Probabilistic packet marking (PPM) is one of the methods on IP traceback, which embeds (i.e., marks) the address of an intermediate router into the header of the sampled packet. However, because the PPM does not have a mechanism to avoid an override of marking, there is a problem that it requires a lot of packets to get the packet mark the router far from the victim node. In this paper we propose a new packet marking scheme which uses the history of previously marked packets to decide for marking the current sampled packet. Through simulation results, we show that our proposed method can reduce the required number of packets significantly to reconstruct the paths for attacking nodes compared with the original PPM

Exact analysis of bit error probability for trellis coded QPSK

This letter presents an exact analysis of bit error probability for trellis coded modulation with soft decision Viterbi decoding. It is shown that this analytical technique is effective for low signal-to-noise power ratio where bounds are useless. The extension to asymmetric constellation is also investigated.

A selective repeat request with continuous multiple transmissions for a message

Automatic repeat request (ARQ) is very effective in error control, and among various ARQs, selective repeat gives the best throughput characteristics where infinite-capacity buffers are theoretically required in the transmitter and receiver stations. Therefore, in practice, a modified selective repeat request method with a finite-capacity buffer must be devised. In this paper, a selective repeat method is proposed where multiple frames corresponding to a message may continuously be sent. Based on the error rate, number of repeats, and round-trip delay time, the appropriate number of multiple transmissions for maximum throughput in the case of a finite-capacity buffer is derived. It is shown that good throughput characteristics can be achieved in the proposed method with an appropriate number of multiple transmissions.

An analytical technique for exact error state probability in soft decision Viterbi decoding

Although Viterbi decoding is widely used in practical systems, only a few studies have been made for exact analysis of error probability. We have previously proposed (see Proc.IEEE International Symposium on Information Theory, Ulm, Germany, p.426, 1997) an analytical technique for the exact analysis of error state probability of 2-state soft decision Viterbi decoding. The extension to bit error probability analysis is possible with error state probability. In this paper, this technique is extended to exact error state probability in 4-state soft decision Viterbi decoding. This employs an iterative calculation of the probability density function of the path metric.

Exact error probability for convolutional codes with soft decision Viterbi decoding

The Viterbi decoding algorithm was proposed as a scheme of decoding convolutional codes, and realizes maximum likelihood decoding. Although a large number of studies have been made on its applications, little is known about its exact error performance. Actually, most of results of error performance studies are based on a bound of error performance or by computer simulation. Only few studies have so far been made for exact analyses, but these results were discussed for hard decisions. In general, it is difficult to exactly analyze the error performance of convolutional codes for soft decisions. The error performance for a high signal-to-noise power ratio (SNR) can be obtained by the error bound, however, little attention has been devoted to the exact error performance for low SNR. In this paper, we propose a new technique for the exact analysis of state probability of convolutional codes with Viterbi decoding. This technique employs an iterative calculation of the probability density function (pdf). The proposed technique gives the exact state probability for low SNR. It can be applied for soft decisions.

QRP07-6: On Inferring Network Impact Factors by Decomposition of Mixed Distribution

An end-to-end round trip time (RTT) is one of the most important communication characteristics for Internet applications. From the viewpoint of network operators, RTT may also become one of the important metrics to understand the network conditions. For this case, we should know how a factor such as network incident influences RTTs. It is obvious that two or more factors may interfere in observed delay characteristics, because packet transmission delays in the Internet are strongly dependent on the time-variant condition of the network. From this reason we previously proposed a modeling method by using mixed distribution which enables to express delay characteristic more accurately where two or more factors which affect network delays exist together. However, this is not clear that how the factors affect the results of measured RTTs, and no investigations have been shown to infer the network behavior based on modeling results. In this paper, we propose an estimation method of network behavior by decomposition of the mixed distribution. Furthermore, in experimental environment, we investigate the influence caused by each network impact factor independently. By applying the proposed method, we also presume the events that occur in network from the measurements of RTTs by using the results of decomposition.

Exact analysis of bit error probability for trellis coded modulation

In this paper, we demonstrate an exact analysis of bit probability for trellis coded modulation by using an analytical technique which is effective even in the region of low signal-to-noise power ratio (SNR). This employs an iterative calculation of probability density function (pdf) of path metric per transition, and is applicable for multilevel coded modulation. We show error performance results of 4-ary trellis coded modulation employing 2-state convolutional encoders.