This work considers two major challenges of modern wireless communication. The first challenge is the analysis and management of interference in multi-user wireless channels. The other challenge is to provide information-theoretic security for future wireless networks. The second chapter considers the first challenge, in particular, the Gaussian interfering multiple access channel (G-IMAC). This channel model is an example of a multi-user interference-affected network. However, even for more simple models, such as the Gaussian interference channel, it is hard to derive good upper bounds and develop achievable schemes to show information-theoretic capacity results. In fact, a complete solution of that channel model is an open problem for over 40 years. However, recent developments have shown that deterministic models can approximate these Gaussian models within a constant-bit gap. These deterministic models view input signals as binary expansion and cut-off the bits which are corrupted by noise. They, therefore, yield insights into the high signal-to-noise regime, where the noise effected signal part has just a minor contribution to the overall capacity and emphasizes the contribution of interference. We, therefore, use the same strategy and look into deterministic approximations of the G-IMAC. We find achievable schemes and converse bounds for arbitrary interference strength and some channel-gain symmetry assumptions. Moreover, we transfer those approximate results to the G-IMAC and show a constant-gap capacity result for this channel model. The most interesting outcome of this work is, that the G-IMAC has multi-user gain. This means that for two users in each cell, half of the interference strength can be used for communication. This is in contrast to the classical Gaussian interference channel (G-IC), where for example treating interference as noise (TIN) is optimal under certain conditions. The G-IMAC, therefore, has an increase in degrees-of-freedom, compared to the G-IC. Chapter 3 considers the second challenge, where we look into the Gaussian multiple access wiretap channel. Here we use similar techniques, namely deterministic approximations, to develop achievable schemes which hold for asymmetric channel gain configurations. Moreover, we develop novel upper bounds, again based on previous insights from the G-IMAC, which are within a constant-gap for certain interference regimes. We then transfer those results to the Gaussian multiple access wiretap channel. For the upper bound of the Gaussian model, we use an in-between approximation and some recent results to provide a bridge between the techniques for the Gaussian model and the linear deterministic model. In Chapter 4 we also consider wireless security, but this time we look into key generation scenarios. We develop a novel deterministic model for key generation with is based on the linear deterministic and the lower triangular deterministic model. It incorporates the key generation viewpoint, i.e. the channel gain is used as a source of randomness for key generation and recovers known results without the tedious state-of-the-art methods. We show that this model gives insights into the previously challenging task of analysing new key generation techniques. Moreover, it can help to communicate the results of information theoretic secrecy analysis with cryptography experts.


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    Titel :

    On deterministic models for capacity approximations in interference networks and information theoretic security


    Weitere Titelangaben:

    Über deterministische Modelle für Kapazitätsapproximationen in Interferenz behafteten Netzwerken und Physical Layer Security


    Beteiligte:

    Erscheinungsdatum :

    2018



    Medientyp :

    Sonstige


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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