Exploiting spatial modulation and analog network coding for the design of energy-efficient wireless networks

As the data rate demands of the cellular users increase, together with their number, it is expected that unprecedented capacity demands should be met in wireless networks in the forthcoming years. However, the energy consumption to meet these rates is expected to increase exponentially, according to trends. This can become a serious issue for both the environment, due to CO2 emissions, and the operators, which will have to pay more for electricity. Hence, several energy-efficient solutions have been proposed, such as multiple antenna systems, dynamic spectrum allocation, heterogeneous networks, and Network Coding, to name a few. Based on the above, the aim of this thesis to propose low-complexity and energy-efficient physical layer-based solutions compared to the already existing approaches, without sacrificing the quality of performance. More specifically, the focus is on the technologies of Spatial Modulation and Analog Network Coding. Both schemes offer the so-called multiplexing gain, which means that multiple streams can be transmitted without sacrificing resources, such as bandwidth. As far as Spatial Modulation is concerned, Spatial Modulation-based schemes are proposed that are more energy efficient than state-of-the-art technologies. Regarding Analog Network Coding, we study its implementation in relay-based scenarios and how it compares in terms of energy efficiency with conventional protocols, such as the time-division multiple access protocol. From the obtained results, the conclusion that can be drawn is that depending on the scenario both Spatial Modulation and Analog Network Coding can provide significant energy gains compared to existing technologies without sacrificing performance.A medida que las demandas de velocidad de datos de los usuarios de redes celulares aumentan, así como su número, se espera que las demandas de capacidad sin precedentes se deban cumplir en las redes inalámbricas en los próximos años. Sin embargo, se espera que aumente de forma exponencial el consumo de energía para satisfacer estas tasas, de acuerdo a las tendencias. Esto puede convertirse en un grave problema ambos para el medio ambiente, debido a las emisiones de CO2, y los operadores, que tendrán que pagar más por la electricidad. Por lo tanto, se han propuesto varias soluciones de eficiencia energética, tales como sistemas de múltiples antenas, la asignación de espectro dinámico, redes heterogéneas, y Network Coding, para nombrar unos pocos. Con base en lo anterior, el objetivo de esta tesis es proponer soluciones de baja complejidad y de eficiencia energética basadas en la capa física, en comparación con los enfoques ya existentes, sin sacrificar la calidad del funcionamiento. Más específicamente, la atención se centra en las tecnologías de Spatial Modulation y Analog Network Coding. Ambos esquemas ofrecen la llamada ganancia de multiplexación, lo que significa que múltiples flujos pueden ser transmitidos sin sacrificar recursos, tales como el ancho de banda. En lo que se refiere a Spatial Modulation, se proponen esquemas basados en Spatial Modulation que son más energéticamente que tecnologías ya existentes. En cuanto a Analog Network Coding, se estudia su aplicación en escenarios inalámbricos basados en relays y cómo se compara en términos de eficiencia energética con los protocolos convencionales, tales como el protocolo de acceso mútiple por división de tiempo. De los resultados obtenidos, la conclusión que se puede extraer es que dependiendo del escenario, ambos Spatial Modulation y Analog Network Coding pueden proporcionar beneficios significativos de energía en comparación con las tecnologías existentes sin sacrificar el funcionamiento

Joint Spatial Division and Multiplexing for FDD in Intelligent Reflecting Surface-assisted Massive MIMO Systems

© 2022 IEEE - All rights reserved. This is the accepted manuscript version of an article which has been published in final form at https://10.1109/TVT.2022.3187656Intelligent reflecting surface (IRS) is a promising technology to deliver the higher spectral and energy requirements in fifth-generation (5G) and beyond wireless networks while shaping the propagation environment. Such a design can be further enhanced with massive multiple-input-multiple-output (mMIMO) characteristics towards boosting the network performance. However, channel reciprocity, assumed in 5G systems such as mMIMO, appears to be questioned in practice by recent studies on IRS. Hence, contrary to previous works, we consider frequency division duplexing (FDD) to study the performance of an IRS-assisted mMIMO system. However, FDD is not suitable for large number of antennas architectures. For this reason we employ the joint spatial division and multiplexing (JSDM) approach exploiting the structure of the correlation of the channel vectors to reduce the channel state information (CSI) uplink feedback, and thus, allowing the use even of a large number of antennas at the base station. JSDM entails dual-structured precoding and clustering the user equipments (UEs) with the same covariance matrix into groups. Specifically, we derive the sum spectral efficiency (SE) based on statistical CSI in terms of large-scale statistics by using the deterministic equivalent (DE) analysis while accounting for correlated Rayleigh fading. Subsequently, we formulate the optimization problem concerning the sum SE with respect to the reflecting beamforming matrix (RBM) and the total transmit power, which can be performed at every several coherence intervals by taking advantage of the slow-time variation of the large-scale statistics. This notable property contributes further to the decrease of the feedback overhead. Numerical results, verified by Monte-Carlo (MC) simulations, enable interesting observations by elucidating how fundamental system parameters such as the rank of the covariance matrix and the number of groups of UEs affect the performance. For example, the selection of a high rank improves the channel conditioning but increases the feedback overhead.Peer reviewe

Adaptive generalized space shift keying

In this article, we propose a closed-loop precoding method for the Generalized Space Shift Keying (GSSK) modulation scheme, suitable for Multiple-Input-Single-Output (MISO) systems and denoted as adaptive GSSK (AGSSK), which achieves transmit-diversity gains in contrast to GSSK. For the case of a perfect feedback channel, we analytically show that for three and four antennas at the transmitter and rates 1 and 2 bits per channel use (bpcu), respectively, a full transmit-diversity can be achieved without reducing the achievable rate. For higher number of transmit antennas and rates, the performance of the proposed scheme degrades due to the smaller average minimum Euclidean distance as the rate increases. Due to this, we, furthermore, propose an enhancing method for AGSSK which relies on the use of time-orthogonal shaping filters for the different constellation points. For the enhanced method, named as AGSSK with time-orthogonal signal design (AGSSK-TOSD), we analytically prove that it offers transmit-diversity gains which are greater than the number of active transmit antennas for any number of transmit antennas and supported rate. This is attained without any antenna subset selection technique, which alleviates the processing burden on the terminal side. Monte Carlo simulations show that AGSSK significantly outperforms GSSK in terms of average bit error probability (ABEP) and, moreover, for medium to high rates and practical signal-to-noise ratio (SNR) regions AGSSK-TOSD outperforms well-known feedback-based multiple-antenna schemes. This advantage of AGSSK-TOSD is further substantiated with an energy effficiency comparison over the conventional schemes for a target (uncoded) ABEP.Peer ReviewedPostprint (published version

Adaptive generalized space shift keying (GSSK) modulation for MISO channels: a new method for high diversity and coding gains

Generalized Space Shift Keying (GSSK) modulation is a recently proposed low-complexity concept for Multiple-Input- Multiple-Output (MIMO) wireless systems. GSSK modulation is a generalized version of Space Shift Keying (SSK) modulation, which provides a better spectral efficiency through multiple active antennas at the transmitter. An apparent weakness of GSSK modulation is that it does not exploit the transmit-antennas to achieve transmit-diversity. In this paper, we propose a precoding method for GSSK modulation, which simultaneously achieves high diversity and coding gains. The solution is based on: i) cophasing the active antennas of each spatial-constellation point; and ii) properly rotating the phases among spatial-constellation points. The new scheme requires Channel State Information at the Transmitter (CSIT), i.e., the channel phases of each wireless link, which can be obtained through a feedback channel. For the case of a perfect feedback channel, we analytically show that for three and four antennas at the transmitter a full transmit diversity can be achieved without reducing the achievable rate. Furthermore, for various MISO configurations and achievable rates we show through Monte Carlo simulations that our proposed scheme outperforms state-of-the-art open-loop GSSK schemes, in terms of both diversity and coding gain, when the number of bits allocated for the quantization of each channel phase is between 2 and 4.Peer ReviewedPreprin

Perpetual Reconfigurable Intelligent Surfaces Through In-Band Energy Harvesting: Architectures, Protocols, and Challenges

Reconfigurable intelligent surfaces (RISs) are considered to be a key enabler of highly energy-efficient 6G and beyond networks. This property arises from the absence of power amplifiers in the structure, in contrast to active nodes, such as small cells and relays. However, still an amount of power is required for their operation. To improve their energy efficiency further, we propose the notion of perpetual RISs, which secure the power needed to supply their functionalities through wireless energy harvesting of the impinging transmitted electromagnetic signals. Towards this, we initially explain the rationale behind such RIS capability and proceed with the presentation of the main RIS controller architecture that can realize this vision under an in-band energy harvesting consideration. Furthermore, we present a typical energy-harvesting architecture followed by two harvesting protocols. Subsequently, we study the performance of the two protocols under a typical communications scenario. Finally, we elaborate on the main research challenges governing the realization of large-scale networks with perpetual RISs.Comment: 7 pages, 8 figure