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In this study, a new modulation method defined as Ramanujan periodic subspace division multiplexing (RPSDM) is proposed using Ramanujan subspaces. Each subspace contains an integer-valued Ramanujan sum and its circular downshifts as a basis. The proposed RPSDM decomposes the linear time-invariant wireless channels into a Toeplitz stair block diagonal matrices, whereas orthogonal frequency division multiplexing (OFDM) decompose the same into diagonal. Advantages of such structured subspaces representation are studied and compared with an OFDM representation in terms of a peak-average power ratio and bit error rate. Zero-forcing and minimum mean square error detectors are applied to evaluate the performance of OFDM and RPSDM techniques. Finally, the simulation results show that the proposed design (with an additional receiver complexity) outperforms OFDM under both detectors.

MassiveMIMO(MaMI) is one of the fiery topics in 5G wireless communications. It is introduced based on the fact that the channel vectors becomes asymptotically orthogonal (as antenna elements tending to infinity). Convergence of frequency selective channel (quasi static block fading) characteristics in terms of favorable propagation and channel hardening (asymptotically orthogonal) conditions are studied using metrics like Eigenvalue Ratio (EVR), Mean Absolute Deviation (MAD) and Diagonal Dominance (DD). Finally, simulations results for convergence metrics EVR, MAD and DD are compared with its limiting behavior. The effect of time delay spread on the channel convergence is studied based on the condition number of channel matrix.

This paper proposes the precoder for Multi User-MassiveMIMO (MU-MaMI) frequency selective broadcast channels with few User Terminals(UTs) having single antenna each. The frequency selective effect of the MaMI channel will be manifested as ISI and IUI. In order to mitigate these interferences and to eliminate the group level decoding of UTs, a precoder is proposed utilizing the block time Channel Impulse Responses (CIRs). This proposed precoder is designed based on the following approaches, Matched Filter(MF), Zero Forcing (ZF), Minimum Mean Square Error (MMSE) and Regularized Channel Inversion (RCI). The performance of these precoders is evaluated using single symbol time (one time symbol) and block time symbols (N time symbols) of each UT. The optimal length N block time symbols and minimum number of Base Station (BS) antennas required for a given N block time and multipath L is evaluated with respect to the Signal-to-Interference Noise Ratio (SINR) asymptotic limits.

3G/4G wireless systems employed multiple antennas at both the transmitter and receiver offered significant gains over single-antenna systems. MassiveMIMO (MM) is one of the 5G technologies, which supports to increase the demand for high speed data, capacity, energy efficiency and spectral efficiency. It is known that space-time multiplexing and/or coding offer attractive means of combating fading and increases the capacity in a multi-antenna communication. In this paper, MM downlink scenario is considered. Performance analysis using conventional precoders like Matched Filter (MF), Zero Forcing (ZF), Regularized Beamforming (RBF) and Minimum Mean Square Error (MMSE) with Singular Value Decomposition (SVD) based balanced equalizer are studied in spatio-temporal environment. Signal to Interference Ratio (SINR) and Bit-Error Rate (BER) are used as performance measures. Monte-Carlo simulations are carried out to compute BER and SINR in MATLAB.