This paper investigates the sum spectral efficiency (SE) and total energy efficiency (EE) of the active reconfigurable intelligent surface (aRIS)-assisted cell-free (CF) massive multiple-input multiple-output (mMIMO) over temporal and spatially correlated channels. Multiple aRISs are deployed between numerous access points (APs) and mobile users to enhance the signals. The active reflective elements (REs) amplify and vary the signal phase. The continuously evolving channel creates a situation, where the channel differs during training and data transmission. We characterize the joint impact of multi-user interference (MUI), pilot contamination (PC), channel aging (CA), and active RIS noise amplification (RNA). The desired signal is enhanced as the reflected signal amplitude and REs per aRIS increase. However, the PC, MUI, CA, and RNA also grow– constraining the SE. Also, the network power consumption increases. An alternating optimization framework based on the weighted minimum mean square error and fractional programming is proposed to optimize the transmit power and reflection coefficients (RCs) with the objective of maximizing the sum SE. It is demonstrated that the number of APs and REs can be reduced by deploying aRISs. The proposed power and RC optimization algorithms considerably improves the sum SE. The trade-off analysis between the total EE and sum SE shows that the envelope of the operating region of the CF mMIMO is expanded by deploying multiple aRISs.

This paper analyzes the spectral efficiency (SE) of an active reconfigurable intelligent surface (RIS)-aided cell-free (CF) massive multiple-input multiple-out (mMIMO). The aggregated channel estimate is derived and the achievable SE is obtained in closed-form by assuming imperfect channel state information. It is shown that the sum SE increases with the number of access points (APs) and reflecting elements (REs). The noise amplification due to active REs escalates the pilot contamination and impairs the sum SE. The active RIS offers higher sum SE than the passive RIS in the extreme scenarios of completely blocked and completely unblocked direct AP-user links.

This paper considers a full-duplex (FD) massive multiple-input multiple-output (mMIMO) system, where both the base station (BS) and user equipment (UE) are equipped with massive transmit antennas. Unlike conventional multi-user linear precoding that treats interference as noise, we integrate ratesplitting multiple access (RSMA), known for better interference management, and its power control policy with FD mMIMO for both uplink and downlink transmission. Assuming imperfect channel state information, closed-form expressions are derived for the achievable sum-rate for the proposed model. Numerical results show that the FD-RSMA demonstrates improved downlink and uplink achievable rates than the conventional multi-user linear precoding scheme.

In this paper, we explore the potential of rate-splitting multiple access (RSMA) in a cell-free (CF) massive multiple-input multiple-output (MIMO) system integrated with low-resolution analog-to-digital converters (ADCs). Both the access points (APs) and the user equipment (UEs) deploy low-resolution ADCs. Thus, quantization noise (QN) limits the system’s performance. The limited coherence interval and the large number of users result in pilot contamination. This arises since multiple users may share the same pilot sequence in the uplink training. We investigate the spectral/energy efficiency (SE/EE) of an RSMA-enabled CF massive MIMO downlink transmission due to the robustness of RSMA against interference. We derive the closed-form SE expressions for the common and private streams which are shown to be exact when compared to Monte Carlo simulations. We optimize the combining weights of the common precoder to maximize the minimum user SE due to the common stream. It is shown that substantial SE gains and higher EE are achieved using the proposed algorithm in the presence of QN and imperfect channel state information. Our results emphasize that RSMA can be adopted to enhance the SE and EE while reducing the quantization bits.

This paper analyzes the spectral/energy efficiency (SE/EE) of a full-duplex (FD) cell-free (CF) massive multiple-input multiple-output (mMIMO) over Rician fading channels. Due to the FD radios, the access points (APs) suffer from self-interference (SI) and inter-AP interference (IAI) while the downlink (DL) users’ signals are corrupted by the uplink (UL) users’ transmissions. We consider the case, where low-resolution analog-to-digital converters (ADCs) are utilized at the APs and DL users, which introduces the quantization noise (QN). The combined effects of Rician$\kappa $-factor, residual SI/IAI, UL-to-DL interference, multi-user interference, and QN on the UL/DL SEs are characterized. The UL SE is degraded by the increase in DL power, whereas the growth in UL power deteriorates the DL SE. The effects of the residual SI/IAI and UL-to-DL interference are worsened by the low-resolution ADCs. We optimize the UL/DL transmit powers to maximize the overall sum SE of the network. It is observed that the proposed power allocation algorithm brings substantial sum SE gain. A trade-off analysis between the EE and SE, as a function of the ADCs’ resolution, shows that the entire envelope of the operating region of FD CF mMIMO is enhanced in Rician channels.

This paper studies the spectral/energy efficiency (SE/EE) of a heterogeneous network with the backhaul enabled by low-resolution analog-to-digital converters (ADCs) quantized full-duplex massive multiple-input multiple-output (MIMO) over Rician channels. Backhaul communication is completed over two phases. During the first phase, the macro-cell (MC) base station (BS) deploys massive receive antennas and a few transmit antennas; the small-cell (SC) BSs employ large-scale receive antennas and a single transmit antenna. For the second phase, the roles of the transmit and receive antennas are switched. Due to the low-resolution ADCs, we account for quantization noise (QN). We characterize the joint impact of the number of antennas, self-interference, SC-to-SC interference, QN, and Rician K-factor. For the first phase, the SE is enhanced with the massive receive antennas and the loss due to QN is limited. For the second phase, the desired signal and QN have the same order. Therefore, the SE saturates with the massive transmit antennas. As the Rician K-factor increases, the SE converges. Power scaling laws are derived to demonstrate that the transmit power can be scaled down proportionally to the massive antennas. We investigate the EE/SE trade-offs. The envelope of the EE/SE region grows with increase in the Rician K-factor.

In this paper, we consider a decode-and-forward (DF) two-way relay (TWR) system in power line communication (PLC). The DF TWR employs physical- layer network coding (PNC). We derive analytic expressions for the average capacity and the outage probability of the system over a log-normal fading channel. Analytic results are verified through Monte Carlo simulations. From the results, the TWR is able to mitigate the half-duplex (HD) spectral efficiency loss incurred by one-way relaying. The impact of the impulsive noise on the system performance is also highlighted in the simulation results. It is shown that higher impulsive probability degrades system performance.

Heterogeneous networks (HetNets) which involves densifying a high powered macro cell (MC) with a number of low powered small cells (SCs), has been identified as key technology for 5G communication. This technology requires that MC is connected to SCs with high speed fiber optic cable for control and coordination. However connecting fiber links to all cells is expensive, labor intensive and less flexible. This paper proposes HetNet topology where massive MIMO with full-duplex (FD) provides wireless backhaul link for SCs. Communication is achieved in two phases. In the first phase, we assume cells in the HetNet are equipped with massive receive antennas and single transmit antennas whereas in the second phase a circulator switches massive antenna receivers into transmitters and single antenna transmitters into receivers. We derive accurate approximations for uplink/downlink (UL/DL) rate under the assumption of imperfect channel state information. Our results indicate that the strength of loop interference (LI) and SC-to-SC interference which occur due to FD operation depends largely on the number of SCs. By increasing the number of SCs, achievable rates also increase but requires more antennas to overcome the deleterious effects of LI and SC-to-SC interference.