The discrete memoryless state-dependent relay channel (SD-RC) is considered in this study. Two main cases are investigated: SD-RC with non-causal channel state information (CSI) and SD-RC with causal CSI. In each case, the SD-RC with partial CSI at the source and the relay is considered. As special cases it includes three different situations in which perfect CSI is available: (i) only at the source, (ii) only at the relay and (iii) both at the source and the relay. For the non-causal situation, the authors establish lower bound on capacity (achievable rate) of the SD-RC, using Gel'fand-Pinsker coding at the nodes informed of CSI and compress-andforward (CF) strategy at the relay. Using the Shannon's strategy and CF relaying, the authors derive lower bound on capacity of SD-RC in the causal case. Furthermore, in order to compare their derived bounds with the previously obtained results, which are based on the decode-and-forward (DF) strategy, the authors consider general Gaussian relay channel (RC) with additive independent and identically distributed Gaussian state and noise, and obtain lower bounds on capacity for the cases in which perfect CSI is available noncausally at the source or at the relay. They also present cases in which their lower bounds outperform DFbased bounds, and can achieve rates close to the upper bound. For causal case, a numerical example of the binary fading Gaussian RC with additive noise is provided.

In this paper, taking into account the effect of link delays, we investigate the capacity region of the Cognitive Interference Channel (C-IFC), where cognition can be obtained from either causal or non-causal generalized feedback. For this purpose, we introduce the Causal Cognitive Interference Channel With Delay (CC-IFC-WD) in which the cognitive user's transmission can depend on L future received symbols as well as the past ones. We show that the CC-IFC-WD model is equivalent to a classical Causal C-IFC (CC-IFC) with link delays. Moreover, CC-IFC-WD extends both genie-aided and causal cognitive radio channels and bridges the gap between them. First, we derive an outer bound on the capacity region for the arbitrary value of L and specialize this general outer bound to the strong interference case. Then, under strong interference conditions, we tighten the outer bound. To derive the achievable rate regions, we concentrate on three special cases: 1) Classical CC-IFC (L = 0), 2) CC-IFC without delay (L = 1), and 3) CC-IFC with unlimited look-ahead in which the cognitive user non-causally knows its entire received sequence. In each case, we obtain a new inner bound on the capacity region. The derived achievable rate regions under special conditions reduce to several previously known results. Moreover, we show that the coding strategy which we use to derive an achievable rate region for the classical CC-IFC achieves the capacity for the classes of degraded and semi-deterministic classical CC-IFC under strong interference conditions. Furthermore, we extend our achievable rate regions to the Gaussian case. Providing some numerical examples for Gaussian CC-IFC-WD, we compare the performances of the different strategies and investigate the rate gain of the cognitive link for different delay values. We show that one can achieve larger rate regions in the "without delay" and "unlimited lookahead" cases than in the classical CC-IFC; this improvement is likely due to the fact that, in the former two cases, the cognitive user can cooperate more effectively with the primary user by knowing the current and future received symbols.Index Terms-Causal cognitive radio, Gel'fand-Pinsker coding, generalized block Markov coding, interference channel, instantaneous relaying, non-causal decode-and-forward. and has published more than 230 technical papers in communication and information theory and cryptography in international journals and conferences proceedings. His current research interests include areas of communication theory, information theory and cryptography with special emphasis on network information theory and security for multiuser wireless communications. At the same time, during his academic activities, he has been involved in different political positions. First Vice President of I. R. Iran, Vice President of I. R. Iran and Head of Management and Planning Organization, Minister of ICT of I. R. Iran and Chancellor of University of Tehran, are the most recent ones.

In this paper, we study a state-dependent relay channel where perfect Channel State Information (CSI) is causally known to transmitters in both symmetric and asymmetric manner. So, three different setups are investigated in which causal CSI is available: 1) at the relay only, 2) at the source only and 3) both at the source and the relay nodes. In each situation, we obtain the lower bound on the capacity (achievable rate) for the general discrete memoryless case. The lower bounds are derived based on Shannon's strategy where CSI is known, and Compress-and-Forward (CF) Strategy at the relay.Index Terms-relay channel, Compress-and-Forward, causal channel state information.

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