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Driven by 5G requirements, research on alternatives to the popular cyclic-prefix orthogonal frequency division multiplexing (CP-OFDM) waveform recently arose. In particular, non-orthogonal circularly filtered waveforms such as generalized frequency division multiplexing (GFDM) were proposed due to flexibility and robustness. Applying multiple-input multiple-output (MIMO) techniques for future wireless networks are unquestionable and thereby compulsory for any alternative waveform. Despite advancements in accurate MIMO detection algorithms for GFDM, compared with CP-OFDM their complexity still exhibited a higher order of magnitude, impeding an energy-efficient implementation. In this paper, we propose a low-complexity formulation for iterative minimum mean squared error with parallel interference cancellation (MMSE-PIC) detection for non-orthogonal waveforms with localized inter-carrier interference, where we focus on the application to MIMO-GFDM. The proposal achieves complexity similar to CP-OFDM and we evaluate its performance under realistic channel conditions with imperfect channel state information, where we obtain up to 2-dB gain of GFDM compared with OFDM. We confirm our findings by analyzing the measured extrinsic information transfer charts and show that the proposal achieves the performance of optimal maximum likelihood detection. The results point out the MMSE-PIC algorithm as a viable technique for iterative MIMO receiver implementations for non-orthogonal waveforms. [ABSTRACT FROM AUTHOR]

This paper studies the link level performance of orthogonal frequency division multiplexing (OFDM) and four other advanced waveforms, namely, filtered OFDM (F-OFDM), universal-filtered OFDM (UF-OFDM), filter bank multicarrier (FBMC) and generalized frequency division multiplexing (GFDM). Compared to OFDM, the two filtered variants achieve lower out-of-band (OOB) emissions and can mostly preserve the conventional OFDM-based transceiver design. For the latter two non-orthogonal waveforms, this paper proposes a low complexity implementation of minimum mean square error equalization to jointly tackle the channel and waveform-induced interference. On this basis, the benefits of FBMC and GFDM can be exploited with complexity comparable to the former (quasi-) orthogonal waveforms. The observed benefits include lower peak-to-average power ratio (PAPR) and smaller frame error rate (FER) under challenging doubly dispersive multiple-input multiple-output (MIMO) fading channels. Additionally, linear filtering of FBMC offers an ultra-low OOB emission, while a good compromise in the usage of time and frequency resources can be achieved by circular filtering of GFDM. In the comparison of offset quadrature amplitude modulation (OQAM) versus QAM for non-orthogonal waveforms, OQAM can offer lower PAPR, while smaller FERs can be achieved by QAM in rich multipath fading channels. [ABSTRACT FROM PUBLISHER]

The coded modulation (CM) capacity represents the maximum achievable data rate for a CM scheme assuming optimal decoding at the receiver. It is an important analytical tool, providing theoretic limits for near-optimum transceiver design. Next generation wireless communications systems with the use of new technologies, such as massive antennas and nonorthogonal waveforms, tend to be large scale. However, the conventional ways developed for evaluating the CM capacity of small-scale systems expose exponential complexity with respect to the system’s input dimension. Therefore, they become infeasible when the input dimension increases by one or two orders of magnitude in large-scale systems of interest. This letter resorts to a lower and upper bound of the CM capacity, allowing for a computationally efficient evaluation with polynomial complexity. In particular, two message passing algorithms, namely expectation propagation (EP) and variational message passing (VMP), are applied to evaluate the bounds. Two applications are examined in the end. The presented results bring valuable information about the system design, allowing one to evaluate the impact of suboptimal implementation in the overall system performance. [ABSTRACT FROM PUBLISHER]

Generalized frequency division multiplexing (GFDM) as a nonorthogonal waveform aims at diverse applications in future mobile networks. To evaluate its performance, its capacity limits are of particular importance. Therefore, this paper analyzes its constellation-constrained capacities for cases where the channel state information (CSI) is unknown at the transmitter and perfectly known at the receiver. In frequency selective channels, GFDM may provide advantage over the conventional orthogonal frequency division multiplexing (OFDM) scheme. In order to achieve near-capacity performance, the interaction of data symbols in time and frequency combined with multiple antennas (MIMO) challenges the design of GFDM receivers. This paper, therefore, applies expectation propagation (EP) for systematic receiver design. It is shown that the resulting iterative MIMO-GFDM receiver with affordable complexity can approach optimum decoding performance and outperform MIMO-OFDM in a rich multipath environment. Simulations are also used to illustrate the impact of channel delay spread on the constellation-constrained capacities and on the performance of the novel receiver algorithm. [ABSTRACT FROM PUBLISHER]