 [19] to quanti- tatively analyze interference in f-OFDM systems, in which the channel matrix is divided into three parts to decompose total inferences into inter-symbol interference (ISI) and adjacent carrier interference (ACI). To better suppress OOB emissions, the filters employed in f-OFDM systems are usually very long (up to half of FFT size [11, 13]), which inevitably leaves the systems prone to in-band interference. The existing works in the literature indicate that it has a trivial influence on system performance for medium to wide subbands [17, 18], and few studies have investigated the performance degradation in narrow subband systems. In this chapter, we will present an analytical model for 3GPP-compatible single band f-OFDM systems, in which the receiver has no knowledge of the transmitter filter [20]. Based on the model, the in-band interference signal is decomposed into ICI, forward ISI (f-ISI), and backward ISI (b-ISI), such that the impact of each interference component can be studied individually; derive an analytical metric to quantify the interference level as a function of several system parameters. This work leads to the development of the condition for in-band interference-free systems, and provides a practical approach for the selection of cyclic redundancy (CR) length to balance system efficiency and receiver complexity. A low-complexity block-based parallel interference cancellation algorithm is then proposed for the in-band interference mitigation. show simulation results for evaluating the performance of f-OFDM with different settings in subband width where the performance of narrow subbands is studied in comparison with wide subbands. The rest of the chapter is organized as follows: Section 2.2 presents the single subband f-OFDM transceiver structure and describes the system model. Section 2.3 analyzes the in-band interference and introduces approaches to suppress the interference. Section 2.4 presents numerical results. Finally, Section 2.5 concludes the chapter. 2.1.1 Notations E{.} 