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Fifth generation (5G) wireless systems are expected to combine emergingtransmission technologies, such as large-scale multiple-input multiple-output(MIMO) and non-orthogonal multi-carrier waveforms, to improve the spectralefficiency and to reduce out-of-band (OOB) emissions. This paper investigatesthe efficacy of two promising multi-carrier waveforms that reduce OOB emissionsin combination with large-scale MIMO, namely filter bank multi-carrier (FBMC)and generalized frequency division multiplexing (GFDM). We develop novel,low-complexity data detection algorithms for both of these waveforms. Weinvestigate the associated performance/complexity trade-offs in the context oflarge-scale MIMO, and we study the peak-to-average power ratio (PAPR). Ourresults show that reducing the OOB emissions with FBMC and GFDM leads to highercomputational complexity and PAPR compared to that of orthogonalfrequency-division multiplexing (OFDM) and single-carrier frequency divisionmultiple access (SC-FDMA).

Linear Large-Scale MIMO Data Detection for 5G Multi-Carrier Waveform Candidates