Resource Allocation for Interference Management in Wireless Networks

Interference in wireless networks is a major problem that impacts system performance quite substantially. Combined with the fact that the spectrum is limited and scarce, the performance and reliability of wireless systems significantly deteriorates and, hence, communication sessions are put at the risk of failure. In an attempt to make transmissions resilient to interference and, accordingly, design robust wireless systems, a diverse set of interference mitigation techniques are investigated in this dissertation. Depending on the rationale motivating the interfering node, interference can be divided into two categories, communication and jamming. For communication interference such as the interference created by legacy users(e.g., primary user transmitters in a cognitive radio network) at non-legacy or unlicensed users(e.g.,secondary user receivers), two mitigation techniques are presented in this dissertation. One exploits permutation trellis codes combined with M-ary frequency shift keying in order to make SU transmissions resilient to PUs’ interference, while the other utilizes frequency allocation as a mitigation technique against SU interference using Matching theory. For jamming interference, two mitigation techniques are also investigated here. One technique exploits time and structures a jammer mitigation framework through an automatic repeat request protocol. The other one utilizes power and, following a game-theoretic framework, employs a defense strategy against jamming based on a strategic power allocation. Superior performance of all of the proposed mitigation techniques is shown via numerical results

Optimized spoofing and jamming a cognitive radio

We examine the performance of a cognitive radio system in a hostile environment where an intelligent adversary tries to disrupt communications by minimizing the system throughput. We investigate the optimal strategy for spoofing and jamming a cognitive radio network with a Gaussian noise signal over a Rayleigh fading channel. We analyze a cluster-based network of secondary users (SUs). The adversary may attack during the sensing interval to limit access for SUs by transmitting a spoofing signal. By jamming the network during the transmission interval, the adversary may reduce the rate of successful transmission. We present how the adversary can optimally allocate power across subcarriers during sensing and transmission intervals with knowledge of the system, using a simple optimization approach specific to this problem. We determine a worst-case optimal energy allocation for spoofing and jamming, which gives a lower bound to the overall information throughput of SUs under attack. © 1972-2012 IEEE

Optimized spoofing and jamming a cognitive radio

We examine the performance of a cognitive radio system in a hostile environment where an intelligent adversary tries to disrupt communications by minimizing the system throughput. We investigate the optimal strategy for spoofing and jamming a cognitive radio network with a Gaussian noise signal over a Rayleigh fading channel. We analyze a cluster-based network of secondary users (SUs). The adversary may attack during the sensing interval to limit access for SUs by transmitting a spoofing signal. By jamming the network during the transmission interval, the adversary may reduce the rate of successful transmission. We present how the adversary can optimally allocate power across subcarriers during sensing and transmission intervals with knowledge of the system, using a simple optimization approach specific to this problem. We determine a worst-case optimal energy allocation for spoofing and jamming, which gives a lower bound to the overall information throughput of SUs under attack. © 1972-2012 IEEE