Information Theoretic Limits of State-dependent Networks

We investigate the information theoretic limits of two types of state-dependent models in this dissertation. These models capture a wide range of wireless communication scenarios where there are interference cognition among transmitters. Hence, information theoretic studies of these models provide useful guidelines for designing new interference cancellation schemes in practical wireless networks. In particular, we first study the two-user state-dependent Gaussian multiple access channel (MAC) with a helper. The channel is corrupted by an additive Gaussian state sequence known to neither the transmitters nor the receiver, but to a helper noncausally, which assists state cancellation at the receiver. Inner and outer bounds on the capacity region are first derived, which improve the state-of-the-art bounds given in the literature. Further comparison of these bounds yields either segments on the capacity region boundary or the full capacity region by considering various regimes of channel parameters. We then study the two-user Gaussian state-dependent Z-interference channel (Z-IC), in which two receivers are corrupted respectively by two correlated states that are noncausally known to transmitters, but unknown to receivers. Three interference regimes are studied, and the capacity region or the sum capacity boundary is characterized either fully or partially under various channel parameters. The impact of the correlation between the states on the cancellation of state and interference as well as the achievability of the capacity is demonstrated via numerical analysis. Finally, we extend our results on the state-dependent Z-IC to the state-dependent regular IC. As both receivers in the regular IC are interfered, more sophisticated achievable schemes are designed. For the very strong regime, the capacity region is achieved by a scheme where the two transmitters implement a cooperative dirty paper coding. For the strong but not very strong regime, the sum-rate capacity is characterized by rate splitting, layered dirty paper coding and successive cancellation. For the weak regime, the sum-rate capacity is achieved via dirty paper coding individually at two receivers as well as treating interference as noise. Numerical investigation indicates that for the regular IC, the correlation between states impacts the achievability of the channel capacity in a different way from that of the Z-IC

CHARACTERIZATION OF FUNDAMENTAL COMMUNICATION LIMITS OF STATE-DEPENDENT INTERFERENCE NETWORKS

Interference management is one of the key techniques that drive evolution of wireless networks from one generation to another. Techniques in current cellular networks to deal with interference follow the basic principle of orthogonalizing transmissions in time, frequency, code, and space. My PhD work investigate information theoretic models that represent a new perspective/technique for interference management. The idea is to explore the fact that an interferer knows the interference that it causes to other users noncausally and can/should exploit such information for canceling the interference. In this way, users can transmit simultaneously and the throughput of wireless networks can be substantially improved. We refer to the interference treated in such a way as ``dirty interference\u27\u27 or noncausal state . Towards designing a dirty interference cancelation framework, my PhD thesis investigates two classes of information theoretic models and develops dirty interference cancelation schemes that achieve the fundamental communication limits. One class of models (referred to as state-dependent interference channels) capture the scenarios that users help each other to cancel dirty interference. The other class of models (referred to as state-dependent channels with helper) capture the scenarios that one dominate user interferes a number of other users and assists those users to cancel its dirty interference. For both classes of models, we develop dirty interference cancelation schemes and compared the corresponding achievable rate regions (i.e., inner bounds on the capacity region) with the outer bounds on the capacity region. We characterize the channel parameters under which the developed inner bounds meet the outer bounds either partially of fully, and thus establish the capacity regions or partial boundaries of the capacity regions

Bounds and capacity theorems for cognitive interference channels with state

Abstract A class of cognitive interference channels with state are investigated, in which a primary transmitter sends a message to two receivers (receivers 1 and 2) with assistance of a cognitive transmitter (that knows the primary transmitter's message), and the cognitive transmitter also sends a separate message to receiver 2. The channel is corrupted by an independent and identically distributed (i.i.d.) state sequence. The scenario, in which the state sequence is noncausally known at both the cognitive transmitter and receiver 2, is first studied. The capacity region is obtained for both the discrete memoryless and Gaussian channels. The second scenario, in which the state sequence is noncausally known only at the cognitive transmitter, is further studied. Inner and outer bounds on the capacity region are obtained for the discrete memoryless channel and its degraded version. The capacity region is characterized for the degraded semideterministic channel and for channels that satisfy a less noisy condition. The Gaussian channels are further studied, which are partitioned into two cases based on how the interference compares with the signal at receiver 1. For each case, inner and outer bounds on the capacity region are derived, and partial boundaries of the capacity region are characterized. The full capacity region is also characterized for channels that satisfy certain conditions. It is shown that certain Gaussian channels achieve the capacity of the same channels with state noncausally known at both the cognitive transmitter and receiver 2