Massive MIMO and mmWave communication are the technologies for achieving 5G design goals. Fortunately, these two technologies share a symbiotic integration. As a result, amalgamating mmWave communications with massive MIMO forms,mmWave-massive MIMO,” which significantly improves spectral and energy efficiency. It also achieves high multiplexing gains and increases mobile network capacity. However, massive MIMO, mmWave communications, and mmWave-massive MIMO systems have been studied independently. Consequently, this article explores the ideas, performances, comparisons, and discussions of these three 5G technologies jointly, considering their precoding and beamforming methods. On the other hand, the complexity of these technologies increases when a large number of antennas and radio frequencies (RFs) are used. Thus, several investigations are going on to search for the appropriate precoding and beamforming strategies with low cost, power, and complexity. Therefore, massive MIMO linear precoding techniques such as zero-forcing, maximum ratio transmission, regularized zero-forcing, truncated polynomial expansion and phased zero forcing are addressed in this work. In addition, the most common non-linear precoding schemes: dirty-paper coding, Tomlinson-Harashima, and vector perturbation, are presented. Furthermore, a detailed discussion of the beamforming techniques called analog, digital, and hybrid analog-digital beamforming schemes is included. We also examine the potential of hybrid analog-digital beamforming with its fully-connected and sub-connected architecture approaches in making mmWave massive MIMO a reality. We evaluate their performance with the parameters: bit error rate, signal to noise ratio, complexity, spectral efficiency, and energy efficiency. According to the analytical and simulation results, the partially-connected hybrid analog/digital beamforming architecture offers better all-over performance for mmWave-Massive MIMO communications by compromising: power consumption, cost, complexity, and performance. Finally, the potential future directions in mmWave-massive MIMO precoding and beamforming challenges are addressed.

https://ieeexplore.ieee.org/ielx7/6287639/9668973/09705623.pdf

Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment

Massive MIMO and mmWave communication are the technologies for achieving 5G design goals. Fortunately, these two technologies share a symbiotic integration. As a result, amalgamating mmWave communications with massive MIMO forms,mmWave-massive MIMO,” which significantly improves spectral and energy efficiency. It also achieves high multiplexing gains and increases mobile network capacity. However, massive MIMO, mmWave communications, and mmWave-massive MIMO systems have been studied independently. Consequently, this article explores the ideas, performances, comparisons, and discussions of these three 5G technologies jointly, considering their precoding and beamforming methods. On the other hand, the complexity of these technologies increases when a large number of antennas and radio frequencies (RFs) are used. Thus, several investigations are going on to search for the appropriate precoding and beamforming strategies with low cost, power, and complexity. Therefore, massive MIMO linear precoding techniques such as zero-forcing, maximum ratio transmission, regularized zero-forcing, truncated polynomial expansion and phased zero forcing are addressed in this work. In addition, the most common non-linear precoding schemes: dirty-paper coding, Tomlinson-Harashima, and vector perturbation, are presented. Furthermore, a detailed discussion of the beamforming techniques called analog, digital, and hybrid analog-digital beamforming schemes is included. We also examine the potential of hybrid analog-digital beamforming with its fully-connected and sub-connected architecture approaches in making mmWave massive MIMO a reality. We evaluate their performance with the parameters: bit error rate, signal to noise ratio, complexity, spectral efficiency, and energy efficiency. According to the analytical and simulation results, the partially-connected hybrid analog/digital beamforming architecture offers better all-over performance for mmWave-Massive MIMO communications by compromising: power consumption, cost, complexity, and performance. Finally, the potential future directions in mmWave-massive MIMO precoding and beamforming challenges are addressed. 

/pdf/precoding-and-beamforming-techniques-in-mmwave-massive-mimo-1vrfsnqx.pdf

Consider a two-user MIMO Gaussian Broadcast Channel with two antennas at the transmitter and two single-antenna receivers. While Dirty Paper Coding (DPC) achieves capacity, its practical adoption needs a precise comparison with the popular method of Zero Forcing Beam Forming (ZFBF). In this work, we obtain a simplified expression for the exact difference in sum rate between DPC and ZFBF at all SNRs. Using this expression, we obtain the distribution of the difference under block fading, and show a significant improvement in rate in wideband OFDM transmission by using DPC for only a small fraction of subcarriers.

Dirty paper coding versus beamforming in multi-user MIMO under OFDM

In this paper, the bit error rate (BER) performance analysis of an underlay cognitive radio (CR) network, which is considered as a broadcast scheme, over fading channels, is investigated. Particularly, the underlay CR network is studied as a closed loop multiple antenna system, presented with dirty paper coding (DPC) approach with the aim of allowing the secondary user (SU) transmission to utilize the spectrum resources efficiently and avoiding harmful interference to the primary user (PU) receiver. The proposed approach is capable of achieving the same performance as that of the zero-forcing (ZF) algorithm over Rayleigh fading channels at the SU receiver. We further show that the BER performance of the PU under Rician fading channel is significantly improved for the proposed study. Finally, numerical and simulation results are provided to demonstrate the performance and corroborate the theoretical analysis.

Broadcast underlay cognitive radio with dirty paper coding over fading channels

The symbol error rate (SER) performance analysis of a broadcast underlay cognitive radio (CR) network, under Nakagami-m fading channels is studied in this paper. Particularly, the unde ...

Broadcast Cognitive Radio with Dirty Paper Coding over Nakagami-m Fading Channel

Dirty paper coding (DPC) is known to achieve the capacity region of a Gaussian Multiple Input Multiple Output-Broadcast channel (MIMO-BC). Practical DPC schemes using finite length codes are still being actively studied. In this paper, we design a zero-forcing DPC (ZF-DPC) scheme using trellis shaping and Low Density Parity Check (LDPC) codes for a MIMO-BC with two transmit antennas and two users (receivers), each with one antenna. This is an extension of an earlier design for the single antenna Gaussian broadcast channel. One of the important aspects of the DPC code design is the introduction of a one block delay that enables the channel encoder (and decoder) and the shaping encoder (and decoder) to operate independently. In the ZF-DPC method, the MIMO precoder ensures that one user has no interference. The other user uses DPC to combat interference. The performance of this method is compared using simulations with the capacity limit and simpler precoder based methods like Minimum Mean Square Error-Vector Perturbation (MMSE-VP) and zero-forcing beamforming (ZF-BF).

/pdf/a-dirty-paper-coding-scheme-for-the-multiple-input-multiple-4mnk4aca7j.pdf

Balakrishna Saradka

Papers

A dirty paper coding scheme for the Multiple Input Multiple Output Broadcast Channel