Capacity allocation in wireless communication networks : models and analyses

This monograph has concentrated on capacity allocation in cellular and Wireless Local Area Networks, primarily with a network operator’s perspective. In the introduc- tory chapter, a reference model has been proposed for the extensive suite of capacity allocation mechanisms that can be applied at different time scales, in order to influ- ence the inherent trade-offs between investment costs, network capacity and service quality. The subsequent chapters presented a number of comprehensive studies with the objective to understand the joint impact of the different control mechanisms on the network operations and service provisioning, as well as the influence of the largely uncontrollable traffic and mobility characteristics on the system- and service-level performance

Semidefinite bounds for mixed binary/ternary codes

For nonnegative integers $n_2, n_3$ and $d$, let $N(n_2,n_3,d)$ denote the maximum cardinality of a code of length $n_2+n_3$, with $n_2$ binary coordinates and $n_3$ ternary coordinates (in this order) and with minimum distance at least $d$. For a nonnegative integer $k$, let $\mathcal{C}_k$ denote the collection of codes of cardinality at most $k$. For $D \in \mathcal{C}_k$, define $S(D) := \{C \in \mathcal{C}_k \mid D \subseteq C, |D| +2|C\setminus D| \leq k\}$. Then $N(n_2,n_3,d)$ is upper bounded by the maximum value of $\sum_{v \in [2]^{n_2}[3]^{n_3}}x(\{v\})$, where $x$ is a function $\mathcal{C}_k \rightarrow \mathbb{R}$ such that $x(\emptyset) = 1$ and $x(C) = 0$ if $C$ has minimum distance less than $d$, and such that the $S(D)\times S(D)$ matrix $(x(C\cup C'))_{C,C' \in S(D)}$ is positive semidefinite for each $D \in \mathcal{C}_k$. By exploiting symmetry, the semidefinite programming problem for the case $k=3$ is reduced using representation theory. It yields $135$ new upper bounds that are provided in tablesComment: 12 pages; some typos have been fixed. Accepted for publication in Discrete Mathematic

Performance analysis of downlink shared channels in a UMTS network

In light of the expected growth in wireless data communications and the commonly anticipated up/downlink asymmetry, we present a performance analysis of downlink data transfer over \textsc{d}ownlink \textsc{s}hared \textsc{ch}annels (\textsc{dsch}s), arguably the most efficient \textsc{umts} transport channel for medium-to-large data transfers. It is our objective to provide qualitative insight in the different aspects that influence the data \textsc{q}uality \textsc{o}f \textsc{s}ervice (\textsc{qos}). As a most principal factor, the data traffic load affects the data \textsc{qos} in two distinct manners: {\em (i)} a heavier data traffic load implies a greater competition for \textsc{dsch} resources and thus longer transfer delays; and {\em (ii)} since each data call served on a \textsc{dsch} must maintain an \textsc{a}ssociated \textsc{d}edicated \textsc{ch}annel (\textsc{a}-\textsc{dch}) for signalling purposes, a heavier data traffic load implies a higher interference level, a higher frame error rate and thus a lower effective aggregate \textsc{dsch} throughput: {\em the greater the demand for service, the smaller the aggregate service capacity.} The latter effect is further amplified in a multicellular scenario, where a \textsc{dsch} experiences additional interference from the \textsc{dsch}s and \textsc{a}-\textsc{dch}s in surrounding cells, causing a further degradation of its effective throughput. Following an insightful two-stage performance evaluation approach, which segregates the interference aspects from the traffic dynamics, a set of numerical experiments is executed in order to demonstrate these effects and obtain qualitative insight in the impact of various system aspects on the data \textsc{qos}

Quality-of-Service differentiation in an integrated services GSM/GPRS network

We develop and analyse a generic model for performance evaluation, parameter optimisation and dimensioning in a \textsc{gsm}/\textsc{gprs} network. The model enables analytical evaluation for a scenario of integrated speech, video and data services, potentially offered in distinct priority classes. While a speech call is assigned a single traffic channel for its entire duration, both video and data calls can handle varying channel assignments. The principal distinction between these elastic call types, is that in case of video calls, a more generous channel assignment implies a better throughput and thus call quality, while for data calls the increased throughput implies a reduced sojourn time. Although a broader variety of models can be designed and analysed within the generic framework, the analytical and numerical results are presented for the \textsc{svd} model integrating speech, video and data calls, and for the \textsc{shl} model, integrating speech and two priority classes of data calls. In both models, an access queue is maintained for data calls which cannot be served immediately upon arrival. Markov chain analysis is applied to derive basic performance measures such as the expected channel utilization, service-specific blocking probabilities (\textsc{gos}), expected video \textsc{qos} (throughput) and expected (priority class-specific) data \textsc{qos} (sojourn times). Furthermore, closed-form expressions are derived for the expected video and data \textsc{qos}, conditional on the call duration or file size, respectively, and on the system state at arrival. As a potential application, these measures can be fed back to the caller as an indication of the expected \textsc{qos}. The included numerical study demonstrates the merit of the presented generic model and performance analysis, and provides \textsc{gsm}/\textsc{gprs} network operators with valuable insight in the \textsc{gos} and \textsc{qos} tradeoffs involved in balancing the various controllable system parameters

Elastic calls in an integrated services network: the greater the call size variability the better the QoS

We study a telecommunications network integrating prioritized stream calls and delay tolerant elastic calls that are served with the remaining (varying) service capacity according to a processor sharing discipline. The remarkable observation is presented and analytically supported that the expected elastic call holding time is decreasing in the variability of the elastic call size distribution. As a consequence, network planning guidelines or admission control schemes that are developed based on deterministic or lightly variable elastic call sizes are likely to be conservative and inefficient, given the commonly acknowledged property of e.g.\ \textsc{www}\ documents to be heavy tailed. Application areas of the model and results include fixed \textsc{ip} or \textsc{atm} networks and mobile cellular \textsc{gsm}/\textsc{gprs} and \textsc{umts} networks. \u

Performance analysis of adaptive scheduling in integrated services UMTS networks

For an integrated services UMTS network serving speech and data calls, we propose, evaluate and compare different scheduling schemes, which dynamically adapt the shared data transport channel rates to the varying speech traffic load. within each cell, the assigned data transfer resources are distributed over the present data flows according to certain fairness objectives. The performance of the adaptive schemes is numerically evaluated by means of analytical performance optimisation methods in combination with Monte Carlo simulations.\ud \u

Semidefinite bounds for nonbinary codes based on quadruples

For nonnegative integers $q,n,d$, let $A_q(n,d)$ denote the maximum cardinality of a code of length $n$ over an alphabet $[q]$ with $q$ letters and with minimum distance at least $d$. We consider the following upper bound on $A_q(n,d)$. For any $k$, let \CC_k be the collection of codes of cardinality at most $k$. Then $A_q(n,d)$ is at most the maximum value of $\sum_{v\in[q]^n}x(\{v\})$, where $x$ is a function \CC_4\to R_+ such that $x(\emptyset)=1$ and $x(C)=0$ if $C$ has minimum distance less than $d$, and such that the \CC_2\times\CC_2 matrix (x(C\cup C'))_{C,C'\in\CC_2} is positive semidefinite. By the symmetry of the problem, we can apply representation theory to reduce the problem to a semidefinite programming problem with order bounded by a polynomial in $n$. It yields the new upper bounds $A_4(6,3)\leq 176$, $A_4(7,4)\leq 155$, $A_5(7,4)\leq 489$, and $A_5(7,5)\leq 87$