In wireless networks, communication links may be subject to random fatal impacts: for example, sensor networks under sudden power losses or cognitive radio networks with unpredictable primary user spectrum occupancy. Under such circumstances, it is critical to quantify how fast and reliably the information can be collected over attacked links. For a single point-to-point channel subject to a random attack, named as a dying channel, we model it as a block-fading (BF) channel with a finite and random channel length. First, we study the outage probability when the coding length K is fixed and uniform power allocation is assumed. Furthermore, we discuss the optimization over K and the power allocation vector PK to minimize the outage probability. In addition, we extend the single point to-point dying channel case to the parallel multi-channel case where each sub-channel is a dying channel, and investigate the corresponding asymptotic behavior of the overall outage probability with two different attack models: the independent-attack case and the m-dependent-attack case. It can be shown that the overall outage probability diminishes to zero for both cases as the number of sub-channels increases if the rate per unit cost is less than a certain threshold. The outage exponents are also studied to reveal how fast the outage probability improves over the number of sub-channels. Besides the information-theoretical results, we also study a practical coding scheme for the dying binary erasure channel (DBEC), which is a binary erasure channel (BEC) subject to a random fatal failure. We consider the rateless codes and optimize the degree distribution to maximize the average recovery probability. In particular, we first study the upper bound of the average recovery probability, based on which we define the objective function as the gap between the upper bound and the average recovery probability achieved by a particular degree distribution. We then seek the optimal degree distribution by minimizing the objective function. A simple and heuristic approach is also proposed to provide a suboptimal but good degree distribution.

In practice, a communication system works with finite blocklength codes because of the delay constraints and the information-theoretic bounds which are proposed for finite blocklength systems can be exploited to determine the performance of a designed system. In this thesis, achievable rates for given average error probabilities are considered for finite blocklength systems. Although classical bounds can be used to upper bound the error probability, these bounds require the optimization of auxiliary variables. In this work, a bound which is called the dependence testing (DT) bound that is free of any auxiliary variables is exploited. The DT bound is evaluated by introducing a normal approximation to the information density. Simulations carried out both for the Gaussian and discrete input alphabets show the proposed approximation enables very good prediction of the achievable rates. The proposed approximation is also used to calculate the average error probability for block fading channels. Simulations performed for Rayleigh block fading channels demonstrate that the total blocklength of the system in addition to the number of fading blocks should be accounted for especially when the number of fading blocks is large. A power allocation problem in block fading channels when the channel state information is available to the transmitting side is investigated in the final part of this work. The DT bound is optimized for a given channel state vector by allocating different power levels to each fading block by exploiting short-term power allocation. A simple power allocation algorithm is proposed which comes out with very similar results compared with the analytically computed values.

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