Capacity Study of Statistical Multiplexing for IP Telephony

Transmitting telephone calls over the Internet causes problems not present in current telephone technology such as packet loss and delay due to queueing in routers. In this undergraduate thesis we study how a Markov modulated Poisson process is applied as an arrival process to a multiplexer and we study the performance in terms of loss probability. The input consists of the superposition of independent voice sources. The predictions of the model is compared with results obtained with simulations of the multiplexer made with a network simulator. The buffer occupancy distribution is also studied and we see how this distribution changes as the load increases

Multi-group frequency hopping OFDMA based on statistical multiplexing

In this paper, the multi-group frequency hopping OFDMA (MG-FH OFDMA) based on the statistical multiplexing is proposed for the downlink cellular system. Compared with the existed random frequency hopping OFDMA (RFH-OFDMA) system utilizing the statistical multiplexing, the proposed MG-FH OFDMA invokes the deterministic hopping pattern to reduce the number of subcarrier collisions. By dividing all users into different groups, the subcarriers are utilized sufficiently. Latin Square hopping pattern and user index updating scheme are applied to randomize the subcarrier collisions among users. The user capacity, defined as the maximum number of users served with a basic data-rate in a cell, is calculated with the consideration of intra-cell capacity and the other cell interference (OCI). Results show that the proposed MG-FH OFDMA achieves higher user capacity than that of the RFH-OFDMA

Statistical Multiplexing and Traffic Shaping Games for Network Slicing

Next generation wireless architectures are expected to enable slices of shared wireless infrastructure which are customized to specific mobile operators/services. Given infrastructure costs and the stochastic nature of mobile services' spatial loads, it is highly desirable to achieve efficient statistical multiplexing amongst such slices. We study a simple dynamic resource sharing policy which allocates a 'share' of a pool of (distributed) resources to each slice-Share Constrained Proportionally Fair (SCPF). We give a characterization of SCPF's performance gains over static slicing and general processor sharing. We show that higher gains are obtained when a slice's spatial load is more 'imbalanced' than, and/or 'orthogonal' to, the aggregate network load, and that the overall gain across slices is positive. We then address the associated dimensioning problem. Under SCPF, traditional network dimensioning translates to a coupled share dimensioning problem, which characterizes the existence of a feasible share allocation given slices' expected loads and performance requirements. We provide a solution to robust share dimensioning for SCPF-based network slicing. Slices may wish to unilaterally manage their users' performance via admission control which maximizes their carried loads subject to performance requirements. We show this can be modeled as a 'traffic shaping' game with an achievable Nash equilibrium. Under high loads, the equilibrium is explicitly characterized, as are the gains in the carried load under SCPF vs. static slicing. Detailed simulations of a wireless infrastructure supporting multiple slices with heterogeneous mobile loads show the fidelity of our models and range of validity of our high load equilibrium analysis

Fronthaul evolution: From CPRI to Ethernet

It is proposed that using Ethernet in the fronthaul, between base station baseband unit (BBU) pools and remote radio heads (RRHs), can bring a number of advantages, from use of lower-cost equipment, shared use of infrastructure with fixed access networks, to obtaining statistical multiplexing and optimised performance through probe-based monitoring and software-defined networking. However, a number of challenges exist: ultra-high-bit-rate requirements from the transport of increased bandwidth radio streams for multiple antennas in future mobile networks, and low latency and jitter to meet delay requirements and the demands of joint processing. A new fronthaul functional division is proposed which can alleviate the most demanding bit-rate requirements by transport of baseband signals instead of sampled radio waveforms, and enable statistical multiplexing gains. Delay and synchronisation issues remain to be solved

On the Statistical Multiplexing Gain of Virtual Base Station Pools

Facing the explosion of mobile data traffic, cloud radio access network (C-RAN) is proposed recently to overcome the efficiency and flexibility problems with the traditional RAN architecture by centralizing baseband processing. However, there lacks a mathematical model to analyze the statistical multiplexing gain from the pooling of virtual base stations (VBSs) so that the expenditure on fronthaul networks can be justified. In this paper, we address this problem by capturing the session-level dynamics of VBS pools with a multi-dimensional Markov model. This model reflects the constraints imposed by both radio resources and computational resources. To evaluate the pooling gain, we derive a product-form solution for the stationary distribution and give a recursive method to calculate the blocking probabilities. For comparison, we also derive the limit of resource utilization ratio as the pool size approaches infinity. Numerical results show that VBS pools can obtain considerable pooling gain readily at medium size, but the convergence to large pool limit is slow because of the quickly diminishing marginal pooling gain. We also find that parameters such as traffic load and desired Quality of Service (QoS) have significant influence on the performance of VBS pools.Comment: Accepted by GlobeCom'1

Markov Models of Statistical Multiplexing of Telephone Dialogue with Packet Switching

Existing methods of analysis of voice transmission by packet switching were designed mainly with respect to a Poisson stream of input packets, for which the probability of an active packet on each input port of the router is a constant value in time. This assumption is not always valid, since the formation of speech packets during a dialogue is a nonstationary process, in which case mathematical modeling becomes an effective method of analysis, through which necessary estimates of a network node being designed for packet transmission of speech may be obtained. This paper presents the result of analysis of mathematical models of Markov chain based speech packet sources vis-à-vis the peculiarities of telephone dialogue models. The derived models can be employed in the design and development of methods of statistical multiplexing of packet switching network nodes

Statistical multiplexing of distributed video streams

National audienceWe consider a media aware network element (MANE) fed by several remote video servers. The role of the MANE is to bufferize the encoded video contents and to build a multiplex containing all video programs to be broadcasted or multicasted over a wireless link. We design a decentralized control technique able to satisfy some video quality fairness constraint among programs. Unlike most statistical multiplexing systems, our scheme is partly decentralized. The bandwidth allocation among programs is centralized and done within the MANE, but takes into account the quality fairness constraint. Each video server is controlled independently from the others, requiring no exchange between servers. The MANE feds back to each video server the level of its associated buffer to help the remote video servers to adapt their rate-distorsion trade-off so that the buffer reaches some reference level. Experimental results show that in the case of Gaussian sources, compressed and delivered to the MANE, an equilibrium is reached, and that the fairness constraint is satisfied

Statistical Multiplexing of H.264 programms

The advent of H.264/AVC is going to change the way Digital Television programs are broadcast. Each program can be independently encoded or jointly encoded resulting thus in a more efficient way to distribute the available channel bandwidth. This paper presents a combined coding scheme for multi-program video transmission in which the channel capacity is distributed among the programs according to the program complexities. A complexity bit rate control algorithm based on the Structural Similarity Index (SSIM) is proposed. SSIM metric is presented under the hypothesis that the Human Visual System (HSV) is very specialized in extracting structural information from a video sequence but not in extracting the errors. Thus, a measurement on structural distortion should give a better correlation to the subjective impression. Current simulations have demonstrated very promising results showing that the algorithm can effectively control the complexity of the multi-program encoding process whilst improving overall subjective