Abstract
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 channel subject to random attacks, named as a dying channel, we model it as a block-fading (BF) channel with a finite and random channel length. For this channel, we first study the outage capacity and the outage probability when the data frame length is fixed and uniform power allocation is assumed. Furthermore, we discuss the optimization over the frame length and/or the power allocation over the constituting data blocks to minimize the outage probability. In addition, we extend the results from the single dying channel to the parallel multi-channel case where each sub-channel is a dying channel, and investigate the asymptotic behavior of the overall outage probability as the number of sub-channels goes to infinity with two different attack models: the independent-attack case and the m-dependent-attack case. It is shown that the asymptotic 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 with the number of sub-channels.