Improper Gaussian signaling for the K-user MIMO interference channels with hardware impairments

This paper investigates the performance of improper Gaussian signaling (IGS) for the K-user multiple-input, multiple-output (MIMO) interference channel (IC) with hardware impairments (HWI). HWI may arise due to imperfections in the devices like I/Q imbalance, phase noise, etc. With I/Q imbalance, the received signal is a widely linear transformation of the transmitted signal and noise. Thus, the effective noise at the receivers becomes improper, which means that its real and imaginary parts are correlated and/or have unequal powers. IGS can improve system performance with improper noise and/or improper interference. In this paper, we study the benefits of IGS for this scenario in terms of two performance metrics: achievable rate and energy efficiency (EE). We consider the rate region, the sum-rate, the EE region and the global EE optimization problems to fully evaluate the IGS performance. To solve these non-convex problems, we employ an optimization framework based on majorization-minimization algorithms, which allow us to obtain a stationary point of any optimization problem in which either the objective function and/or constraints are linear functions of rates. Our numerical results show that IGS can significantly improve the performance of the K-user MIMO IC with HWI and I/Q imbalance, where its benefits increase with the number of users, K, and the imbalance level, and decrease with the number of antennas.The work of Mohammad Soleymani and Peter J. Schreier was supported by the German Research Foundation (DFG) under Grant SCHR 1384/8-1. The work of Ignacio Santamaria was supported in part by Ministerio de Ciencia e Innovacion of Spain, and in part by AEI/FEDER funds of the E.U. under Grants TEC2016-75067-C4-4-R (CARMEN) and PID2019-104958RB-C43 (ADELE)

NOMA-based improper signaling for multicell MISO RIS-assisted broadcast channels

In this paper, we study the performance of reconfigurable intelligent surfaces (RISs) in a multicell broadcast channel (BC) that employs improper Gaussian signaling (IGS) jointly with non-orthogonal multiple access (NOMA) to optimize either the minimum-weighted rate or the energy efficiency (EE) of the network. We show that although the RIS can significantly improve the system performance, it cannot mitigate interference completely, so we have to employ other interference-management techniques to further improve performance. We show that the proposed NOMA-based IGS scheme can substantially outperform proper Gaussian signaling (PGS) and IGS schemes that treat interference as noise (TIN) in particular when the number of users per cell is larger than the number of base station (BS) antennas (referred to as overloaded networks). In other words, IGS and NOMA complement to each other as interference management techniques in multicell RIS-assisted BCs. Furthermore, we consider three different feasibility sets for the RIS components showing that even a RIS with a small number of elements provides considerable gains for all the feasibility sets.The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Sangarapillai Lambotharan. The work of Ignacio Santamaria was supported by the Project ADELE funded by MCIN/ AEI /10.13039/501100011033, under Grant PID2019-104958RB-C43. The work of Eduard Jorswieck was supported by the Federal Ministry of Education and Research (BMBF, Germany) through the Program of Souverän. Digital. Vernetzt.” joint Project 6G-RIC, under Grants 16KISK020K and 16KISK031

Rate splitting in MIMO RIS-assisted systems with hardware impairments and improper signaling

In this paper, we propose an optimization framework for rate splitting (RS) techniques in multiple-input multiple-output (MIMO) reconfigurable intelligent surface (RIS)-assisted systems, possibly with I/Q imbalance (IQI). This framework can be applied to any optimization problem in which the objective and/or constraints are linear functions of the rates and/or transmit covariance matrices. Such problems include minimum-weighted and weighted-sum rate maximization, total power minimization for a target rate, minimum-weighted energy efficiency (EE) and global EE maximization. The framework may be applied to any interference-limited system with hardware impairments. For the sake of illustration, we consider a multicell MIMO RIS-assisted broadcast channel (BC) in which the base stations (BSs) and/or the users may suffer from IQI. Since IQI generates improper noise, we consider improper Gaussian signaling (IGS) as an interference-management technique that can additionally compensate for IQI. We show that RS when combined with IGS can substantially improve the spectral and energy efficiency of overloaded networks (i.e., when the number of users per cell is larger than the number of transmit/receive antennas).The work of Ignacio Santamaria has been partly supported by the project ADELE PID2019-104958RB-C43, funded by MCIN/AEI/10.13039/501100011033. The work of Eduard Jorswieck was supported in part by the Federal Ministry of Education and Research (BMBF, Germany) in the program of “Souver¨an. Digital. Vernetzt.” joint project 6G-RIC, project identification number: 16KISK020K and 16KISK031

Non-Orthogonal Multiple Access with Improper Gaussian Signaling

© 2007-2012 IEEE. Improper Gaussian signaling (IGS) helps to improve the throughput of a wireless communication network by taking advantage of the additional degrees of freedom in signal processing at the transmitter. This paper exploits IGS in a general multiuser multi-cell network, which is subject to both intra-cell and inter-cell interference. With IGS under orthogonal multiple access (OMA) or non-orthogonal multiple access (NOMA), designs of transmit beamforming to maximize the users' minimum throughput subject to transmit power constraints are addressed. Such designs are mathematically formulated as nonconvex optimization problems of structured matrix variables, which cannot be solved by popular techniques such as weighted minimum mean square error or convex relaxation. By exploiting the lowest computational complexity of 2× 2 linear matrix inequalities, lower concave approximations are developed for throughput functions, which are the main ingredients for devising efficient algorithms for finding solution of these difficult optimization problems. Numerical results obtained under practical scenarios reveal that there is an almost two-fold gain in the throughput by employing IGS instead of the conventional proper Gaussian signaling under both OMA and NOMA; and NOMA-IGS offers better throughput compared to that achieved by OMA-IGS