• Energy Research

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. accepted

This paper proposes a general optimization framework for rate splitting multiple access (RSMA) in beyond diagonal (BD) reconfigurable intelligent surface (RIS) assisted ultra-reliable low-latency communications (URLLC) systems. This framework can provide a suboptimal solution for a large family of optimization problems in which the objective and/or constraints are linear functions of the rates and/or energy efficiency (EE) of users. Using this framework, we show that RSMA and RIS can be mutually beneficial tools when the system is overloaded, i.e., when the number of users per cell is higher than the number of base station (BS) antennas. Additionally, we show that the benefits of RSMA increase when the packets are shorter and/or the reliability constraint is more stringent. Furthermore, we show that the RSMA benefits increase with the number of users per cell and decrease with the number of BS antennas. Finally, we show that RIS (either diagonal or BD) can highly improve the system performance, and BD-RIS outperforms regular RIS. Accepted at IEEE Transaction of Wireless Communications

Improper Gaussian signaling (IGS) has been used as an effective interference management tool in interference limited systems. Improper Gaussian signals are correlated with their complex conjugates. In this paper, we investigate the optimality of IGS from an energy efficiency (EE) perspective. First, we obtain closed form optimality conditions for IGS.We then leverage these conditions to devise a bisection method that finds the optimal transmission parameters. Our results show that IGS can improve the EE of an underlay cognitive radio system. The work of M. Soleymani, C. Lameiro and P. J. Schreier was supported by the German Research Foundation (DFG) under grants LA 4107/1-1 and SCHR 1384/8-1. The work of I. Santamaria has been partially supported by MINECO of Spain and AEI/FEDER funds of the E.U., under grant TEC2016-75067-C4-4-R (CARMEN).

This paper proposes a general optimization framework to improve the spectral and energy efficiency (EE) of ultra-reliable low-latency communication (URLLC) simultaneous-transfer-and-receive (STAR) reconfigurable intelligent surface (RIS)-assisted interference-limited systems with finite block length (FBL). This framework can solve a large variety of optimization problems in which the objective and/or constraints are linear functions of the rates and/or EE of users. Additionally, the framework can be applied to any interference-limited system with treating interference as noise as the decoding strategy at receivers. We consider a multi-cell broadcast channel as an example and show how this framework can be specialized to solve the minimum-weighted rate, weighted sum rate, global EE and weighted EE of the system. We make realistic assumptions regarding the (STAR-)RIS by considering three different feasibility sets for the components of either regular RIS or STAR-RIS. Our results show that RIS can substantially increase the spectral and EE of URLLC systems if the reflecting coefficients are properly optimized. Moreover, we consider three different transmission strategies for STAR-RIS as energy splitting (ES), mode switching (MS), and time switching (TS). We show that STAR-RIS can outperform a regular RIS when the regular RIS cannot cover all the users. Furthermore, it is shown that the ES scheme outperforms the MS and TS schemes. Accepted at IEEE ACCESS

This paper studies the performance of improper Gaussian signaling (IGS) in a multicell broadcast multiple-input, multiple-output (MIMO) reconfigurable-intelligent-surface (RIS)-assisted channel. The transceivers are non-ideal devices with I/Q imbalance, which further motivates the use of IGS. We propose IGS schemes to improve the spectral and energy efficiency (EE) of the system by solving different optimization problems such as minimum-weighted-rate, weighted-sum-rate, minimum-weighted-EE and global-EE maximization. Two different RIS implementations are considered: in the first one, the phase and amplitude of the RIS components can be optimized independently, which provides an upper-bound for RIS performance. In the second implementation, the amplitude of each RIS component is fixed, and only its phase can be optimized, which is referred to as reflecting surfaces. We show that RIS can significantly increase the spectral and energy efficiency of the system, while the reflecting surfaces perform very close to the upper-bound performance of RISs. Moreover, distributed RIS implementations that use spatially separated RIS with fewer components, can outperform centralized implementations consisting of a single RIS with co-located reflecting elements. Additionally, our results indicate that IGS can provide considerable gains from both spectral and energy-efficiency perspectives, and the benefits of IGS can be even higher in RIS-assisted systems. The work of Ignacio Santamaria was supported in part by MCIN/AEI (10.13039/501100011033) through the Project ADELE under Grant PID2019-104958RB-C43. The work of Mohammad Soleymani and Peter Schreier was supported in part by the German Research Foundation (DFG) under contract SCHR 1384/7-1.

This paper proposes an energy-efficient scheme for multicell multiple-input, multiple-output (MIMO) simultaneous transmit and reflect (STAR) reconfigurable intelligent surfaces (RIS)-assisted broadcast channels by employing rate splitting (RS) and improper Gaussian signaling (IGS). Regular RISs can only reflect signals. Thus, a regular RIS can assist only when the transmitter and receiver are in the reflection space of the RIS. However, a STAR-RIS can simultaneously transmit and reflect, thus providing a 360-degrees coverage. In this paper, we assume that transceivers may suffer from I/Q imbalance (IQI). To compensate for IQI, we employ IGS. Moreover, we employ RS to manage intracell interference. We show that RIS can significantly improve the energy efficiency (EE) of the system when RIS components are carefully optimized. Additionally, we show that STAR-RIS can significantly outperform a regular RIS when the regular RIS cannot cover all the users. We also show that RS can highly increase the EE comparing to treating interference as noise. Accepted at the 31st European Signal Processing Conference (EUSIPCO 2023)

This paper investigates the energy efficiency (EE) of improper Gaussian signaling (IGS) in a K-user interference channel (IC). IGS allows unequal variances and/or correlation between the real and imaginary parts, and it has recently been shown to be advantageous in various interference-limited scenarios. In this paper, we propose an energy-efficient IGS design for the K-user IC, which is based on a separate optimization of the powers and complementary variances of the users. We compare the EE region achieved by the proposed scheme with that achieved by conventional proper signaling and show that IGS can significantly improve the EE region. The work of M. Soleymani, C. Lameiro and P. J. Schreier was supported by the German Research Foundation (DFG) under grants SCHR1384/8-1 and LA 4107/1-1. The work of I. Santamaria was supported by the Ministerio de Economía y Competitividad (MINECO) and AEI/FEDER funds of the UE,Spain, under project CARMEN (TEC2016-75067-C4-4-R).

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). accepted at IEEE Transaction on Vehicular Technology