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Motivated by 5G application requirements that challenge the use of orthogonal frequency division multiplexing (OFDM), non-orthogonal multi-carriers are being investigated. Unlike OFDM that takes advantage of orthogonal pilot observation, in non-orthogonal waveforms, pilots are contaminated by interference from multiple dimensions, i.e., inter-subsymbol-, inter-carrier-, and inter-antenna-interference, when multiple-input-multiple-output (MIMO) is also part of the transmission. Employing cyclic-prefix (CP) in multi-carrier systems not only protects the signal from inter-symbol-interference but also allows circular interpretations of the channel, which simplifies the estimation and equalization techniques. Nevertheless, the CP information is usually discarded at the receiver side. In this paper, by considering the fact that non-orthogonal waveforms suffer from multiple dimensions of interference, we derive a MIMO linear-minimum-mean-squared-error (LMMSE)-based parallel-interference-cancellation (PIC) method for joint channel estimation and equalization of non-orthogonal waveforms. Unlike the common practice, by properly localizing the pilots in time domain, we also use the pilots’ information from CP. We apply our proposed algorithm to a flexible non-orthogonal waveform known as generalized frequency division multiplexing (GFDM). Taking advantage of block-circularity of GFDM, we investigate the complexity aspects for such CP-aided LMMSE-PIC channel estimation. Through simulation results, we show that using CP information of pilots for GFDM gains up to 2.4-dB better frame error rate performance than an OFDM signal. [ABSTRACT FROM AUTHOR]

In this paper, a graph-based soft iterative receiver (GSIR) for fast fading channels is investigated. Soft channel estimation as well as soft-output data detection are jointly accomplished via Bayesian inference over a general factor graph. The key feature is a transfer node which enables information flow from one channel node to adjacent channel nodes. The performance characteristics of this receiver is investigated via an EXIT chart analysis and simulation results. Particular emphasis is on a proper channel code design. The algorithm is universally applicable to arbitrary (bijective and non-bijective) modulation formats and can easily be extended to multi-dimensional channel estimation. [ABSTRACT FROM PUBLISHER]

Co-channel interference (CCI) occurs in a wireless receiver when multiple signals are present. The receiver experiences excessive CCI under overload which occurs when there are more signals than receive antennas. This makes separation and estimation of the transmitted data signals difficult. We develop a novel reduced-complexity receiver structure for the separation and symbol detection of multiple co-channel signals in frequency-flat Rayleigh fading channels. Moreover, we show that list-based group-wise processing can achieve better performance at low and moderate signal-to-noise ratios than existing group-wise soft information processing schemes. The receiver is equipped with multiple antennas and developed to work under overload. Its structure consists of a linear preprocessor followed by a nonlinear reduced-complexity symbol detector. The proposed list group-search detection (LGSD) algorithm relies on list feedback and reduces complexity by iteratively searching over groups of transmitted symbols. It outputs a list of likely data symbols which is well suited to further processing using soft input error control decoders. Simulation shows that LGSD can achieve near optimum joint maximum likelihood performance under overload at significantly lower complexity. [ABSTRACT FROM PUBLISHER]