Non-orthogonal multiple access (NOMA) has been envisioned as a promising multiple access technique for 5G and beyond wireless networks due to its significant enhancement of spectral efficiency. In this paper, we investigate a robust energy efficiency design for multiuser multiple-input singleoutput (MISO) NOMA systems where imperfect channel state information is available at the base station. A clustering algorithm is applied to group the users into different clusters, and then NOMA technique is employed to share the available resources fairly among the users in each cluster. To remove the interference between clusters, two different types of zero-forcing (ZF) designs, namely, hybrid-ZF and full-ZF are employed at the BS. The full-ZF scheme completely removes the interference leakage at the cost of more number of antennas and the hybrid-ZF scheme partially mitigates the interference leakage. To solve the problem, the Dinkelbach's algorithm is employed to convert the non-linear fractional programming problem into a simple subtractive form. Finally, simulation results reveal that hybrid-ZF outperforms the full-ZF scheme with a few clusters, while full-ZF shows a better performance with the higher number of clusters. The numerical results confirm that our proposed robust scheme outperforms the non-robust scheme in terms of the rate-satisfaction ratio at each user.

Abstract-The development of 5G enabling technologies brings new challenges to the design of power amplifiers (PAs). In particular, there is a strong demand for low-cost, nonlinear PAs which, however, introduce nonlinear distortions. On the other hand, contemporary expensive PAs show great power efficiency in their nonlinear region. Inspired by this trade-off between nonlinearity distortions and efficiency, finding an optimal operating point is highly desirable. Hence, it is first necessary to fully understand how and how much the performance of multiple-input multipleoutput (MIMO) systems deteriorates with PA nonlinearities. In this paper, we first reduce the ergodic achievable rate (EAR) optimization from a power allocation to a power control problem with only one optimization variable, i.e. total input power. Then, we develop a closed-form expression for the EAR, where this variable is fixed. Since this expression is intractable for further analysis, two simple lower bounds and one upper bound are proposed. These bounds enable us to find the best input power and approach the channel capacity. Finally, our simulation results evaluate the EAR of MIMO channels in the presence of nonlinearities. An important observation is that the MIMO performance can be significantly degraded if we utilize the whole power budget.

Massive multiple-input multiple-output (MIMO) relaying is a promising technological paradigm which can offer high spectral efficiency and substantially improved coverage. Yet, these configurations face some formidable challenges in terms of digital signal processing (DSP) power consumption and circuitry complexity, since the number of radio frequency (RF) chains may scale with the number of antennas at the relay station. In this paper, we advocate that performing a portion of the power-intensive DSP in the analog domain, using simple phase shifters and with a reduced number of RF paths, can address these challenges. In particular, we consider a multipair amplify-and-forward (AF) relay system with maximum ratio combining/transmission (MRC/MRT) and we determine the asymptotic spectral efficiency for this hybrid analog/digital architecture. After that, we extend our analytical results to account for heavily quantized analog phase shifters and show that the performance loss with 2 quantization bits is only 10%.

Abstract-Massive multiple-input multiple-output (MIMO) avails of simple transceiver design which can tackle many drawbacks of relay systems in terms of complicated signal processing, latency, and noise amplification. However, the cost and circuit complexity of having one radio frequency (RF) chain dedicated to each antenna element are prohibitive in practice. In this paper, we address this critical issue in amplify-andforward (AF) relay systems using a hybrid analog and digital (A/D) transceiver structure. More specifically, leveraging the channel long-term properties, we design the analog beamformer which aims to minimize the channel estimation error and remain invariant over a long timescale. Then, the beamforming is completed by simple digital signal processing, i.e., maximum ratio combining/maximum ratio transmission (MRC/MRT) or zero-forcing (ZF) in the baseband domain. We present analytical bounds on the achievable spectral efficiency taking into account the spatial correlation and imperfect channel state information at the relay station. Our analytical results reveal that the hybrid A/D structure with ZF digital processor exploits spatial correlation and offers a higher spectral efficiency compared to the hybrid A/D structure with MRC/MRT scheme. Our numerical results showcase that the hybrid A/D beamforming design captures nearly 95% of the spectral efficiency of a fully digital AF relaying topology even by removing half of the RF chains. It is also shown that the hybrid A/D structure is robust to coarse quantization, and even with 2-bit resolution, the system can achieve more than 93% of the spectral efficiency offered by the same hybrid A/D topology with infinite resolution phase shifters.