Dmitri Moltchanov

We consider the state of the wireless channel in terms of the covariance stationary signal-to-noise ratio (SNR) process and parameterize it using the probability distribution function of SNR and lag-1 autocorrelation coefficient of associated autocorrelation function (ACF). In order to discriminate the state of the wireless channel we apply methods of statistical process control. Particularly, we use exponential weighted moving average (EWMA) change-point statistical test to detect shifts in the mean of the SNR process. The proposed approach is verified using SNR measurements of IEEE 802.11b wireless channel.

IntroductionMobile and wireless communication systems are becoming more and more complex, making understanding the interaction of different technologies on different layers a very difficult task. The introduction of sophisticated techniques on the physical layer that react to changes of the wireless channel on small timescales requires new paradigms for modeling, simulating, and analyzing current and future wireless networks. Investigating the relationship of new physical layer techniques, application-specific requirements and performance measures will become a major research topic for future wireless networks. A continuous change in the methodology for evaluating the network performance takes place in the Internet. In the past, network performance was mainly evaluated using concretely measurable values like packet loss rate, delay, or jitter. The current trend in the Internet goes toward application-specific quality measures that judge more the subjective experience of the end user th ...

We propose an analytical model for a TCP SACK connection running over a wireless channel with completely reliable ARQ/FEC. We develop the model in two steps. At the first step, we consider the service process of the wireless channel and derive the probability distribution function of the time required to successfully transmit a single IP packet over the wireless channel. This distribution is used at the next step of the modeling where we derive the expression for TCP SACK steady state goodput. The developed model allows to quantify the effect of many implementation-specific parameters on TCP performance in wireless domain. We also demonstrate that TCP spurious timeouts, reported in many empirical studies, do not occur when wireless channel conditions are stationary and their presence in empirical measurements should be attributed to non-stationary behavior of wireless channel characteristics.

In this paper we consider call admission control in cellular environment for data sessions and voice calls of high priority. A cell is divided into two zones with different average signal to noise ratio, and each zone uses its own modulation and coding. A dynamic resource allocation scheme is further considered, which allows communication systems to utilize their resources more efficiently. All the idle channels, which are left after the voice calls, are allocated to elastic data sessions to increase their transmission rate. When a voice call arrives, required channels can be released to serve it if only elastic data calls have a minimum required bandwidth to continue their sessions. To evaluate the role of elastic traffic, analytical models with elastic and fixed data sessions are formulated and solved. For both cases we derive blocking probabilities as well as other performance metrics of interest. According to numerical results, elastic data sessions achieve higher channel utilization and their mean transmission time is ten times less than that of fixed data sessions. As a result, the mean number of elastic data sessions in the system is twice less than that of fixed data sessions.

We propose simple and computationally efficient wireless channel modeling algorithm. For this purpose we adopt the special case of the algorithm initially proposed in [1] and show that its complexity significantly decreases when the time-series is covariance stationary binary in nature. We show that for such time-series the solution of the inverse eigenvalue problem returns unique transition probability matrix of the modulating Markov chain that is capable to match statistical properties of empirical frame error processes. Our model explicitly takes into account autocorrelational and distributional properties of empirical data. We validate our model against empirical frame error traces of IEEE 802.11b wireless access technology operating in DCF mode over spread spectrum at 2Mbps and 5.5 Mbps bit rates. We also made available the C code of the model as well as pre-compiled binaries for Linux and Windows operating systems at http://www.cs.tut.fi/~moltchan.

Providing reliable data communications over wireless channels is a challenging task because time-varying wireless channel characteristics often lead to bit errors. These errors result in loss of IP packets and, consequently, TCP segments encapsulated into these packets. Since TCP cannot distinguish packet losses due to bit corruption from those due to network congestion, any packet loss caused by wireless channel impairments leads to unnecessary execution of the TCP congestion control algorithms and, hence, sub-optimal performance. Automatic Repeat reQuest (ARQ) and Forward Error Correction (FEC) try to improve communication reliability and reduce packet losses by detecting and recovering corrupted bits. Most analytical models that studied the effect of ARQ and FEC on TCP performance assumed that the ARQ scheme is perfectly persistent (i.e., completely reliable), thus a frame is always successfully transmitted irrespective of the number of transmission attempts it takes. In this paper, we develop an analytical cross-layer model for a TCP connection running over a wireless channel with a semi-reliable ARQ scheme, where the amount of transmission attempts is limited by some number. The model allows to evaluate the joint effect of stochastic properties of the wireless channel characteristics and various implementation-specific parameters on TCP performance, which makes it suitable for performance optimization studies. The input parameters include the bit error rate, the value of the normalized autocorrelation function of bit error observations at lag 1, the strength of the FEC code, the persistency of ARQ, the size of protocol data units at different layers, the raw data rate of the wireless channel, and the bottleneck link buffer size.

Emerging multimedia services are becoming very attractive for next-generation wireless networks. However, both limited quality of service (QoS) support and lack of bandwidth at the air interface restrain their wide deployment in current evolution of third generation (3G) wireless systems. Mp3-based entertainment applications, such as file downloading and streaming which are common nowadays in the Internet, are supposed to be very challenging and demanding services for next- generation wireless networks. In this paper we consider mp3 traffic delivery using two wireless access technologies, which are claimed to be used in next generation wireless networks, wireless local area network (WLAN) and general packet radio service (GPRS). We provide our experiments under different user's mobility patterns and compare the QoS of these services provided through wireless access with local area network (LAN) access technology. Additionally, we practically investigate peculiarities and specific issues arising in QoS assurance for both mp3 streaming and downloading services.

From 1 to 4 December, the IEEE Global Communications Conference 2008 (IEEE GLOBECOM) was held in New Orleans, Louisiana, United States. New Orleans was hosting GLOBECOM for the second time, the first having been in 1985, and in order to account for the enormous changes in the communications industry that have happened since, ComSoc's flagship conference was themed "Building A Better World Through Communications."

Client relay is a promising technology to improve the performance of the cell-edge clients in a wireless cellular network. Unfortunately, there is a lack of performance analysis results for client relay networks in the research literature. This is mainly due to extremely complex interactions between network, data link and physical layers. In this paper we fill in this gap by

The Measurement-based Admission Control algorithm presented in this paper has been devised to overcome three shortcomings. Firstly, its configuration parameter strictly correspond to standard QoS definitions in Service Level Agreements, namely packet loss probability. While this is featured by alternative designs too, the second issue, that of considerable performance fluctuations under varying traffic conditions, is a rather general problem. Applying a non-parametric approach the presented algorithm’s estimation model is free from assumptions and simulations assert consistent performance for a set of various conditions. Finally, the third improvement is certainly most appealing, the algorithm’s independence from fine-tuning. In fact, the optimal value of the performance determining parameter is being estimated from the measured sample. This makes the algorithm highly adaptive as well as autonomous and simulations confirm near optimal performance and accuracy.

An intention to adopt IP protocol for future mobile communication and subsequent extension of Internet services to the air interface calls for advanced performance modeling approaches. To provide a tool for accurate performance evaluation of IP-based applications running over the wireless channels we propose a novel cross-layer wireless channel modeling approach. We extend the small-scale propagation model representing the received signal strength to IP layer using the cross-layer mappings. Proposed model is represented by the IP packet error process and retains memory properties of initial signal strength process. Contrarily to those approaches developed to date, our model requires less restrictive assumptions regarding behavior of the small-scale propagation model at layers above physical. We compare results obtained using our model with those, published to date, and show that our approach allows to get more accurate estimators of IP packet error probabilities.