The scarcity of the radio spectrum and the increasing demand on bandwidth makes it vital to optimize the spectrum use. While a maximum efficiency should be attained, a minimal interference level should be maintained. OFDM has been selected as the modulation scheme in several wireless standards. Channel estimation is a fundamental task in OFDM and it becomes even more challenging in the presence of interference. In this thesis, our aim is to propose channel estimation algorithms for OFDM systems in the presence of interference, where conventional channel estimators designed for OFDM fail. First, we consider the cognitive radio environment and propose a novel channel estimation framework for fast time-varying channels in OFDM with NBI. This is accomplished through an expectation maximization (EM) based algorithm. This formulation allows us to obtain a closed-form expression for the estimation of the noise power. In this thesis, we are particularly interested in a very recent scheme of superimposed pilots for OFDM (DNSP). DNSP assures interference-free pilots at the expense of data interference. Seen the modernity of DNSP, a suitable receiver has to be designed to cope with its design. We first propose a low-complexity interference canceler (IC) for slow time-varying channels with DNSP. The performance of the proposed IC is guaranteed when the channel estimation error is small. As another contribution, we extend the design of the approximated IC for DNSP so as to take the channel estimation errors into account. Finally, we consider robust channel estimation which can be viewed as one of the perspectives of this thesis.