1,040 research outputs found

    Heuristic antenna selection and precoding for a massive MIMO system

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    Sixth Generation (6G) transceivers are envisioned to feature massively large antenna arrays compared to its predecessor. This will result in even higher spectral efficiency (SE) and multiplexing gains. However, immense concerns remain about the energy efficiency (EE) of such transceivers. This work focuses on partially connected hybrid architectures, with the primary aim of enhancing the EE of the system. To achieve this objective, the study proposes a combined approach of joint antenna selection and precoding, which holds the potential to further optimize the system’s EE while maintaining a satisfactory SE performance levels. The proposed approach incorporates antenna selection based on a meta-heuristic cyclic binary particle swarm optimization algorithm along with successive interference cancellation-based precoding. The results indicate that the proposed solution, in terms of SE and EE, performs very close to the optimal exhaustive search algorithm. This study also investigates the trade-off between SE and EE in a low and high signal-to-noise ratio (SNR) regimes. The robustness of the proposed scheme is also demonstrated when the channel state information is imperfect. In conclusion, this work presents a lower complexity approach to enhance EE in 6G transceivers while maintaining SE performance and along with a reduction in power consumption

    Decoupled UL/DL User Association in Wireless-Powered HetNets with Full-Duplex Small Cells

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    In this paper, we propose two downlink (DL)-uplink (UL) decoupled (DUDe) user association schemes in wireless-powered full-duplex (FD) heterogeneous networks (HetNets). We consider a two-tier HetNet comprising of half-duplex (HD) massive multi-antenna macrocell base stations (MBSs) and dual-antenna FD small cell base stations (SBSs) to support UL and DL transmissions of FD user equipments (UEs). Each FD UE is first associated to one MBS/SBS, based on the mean maximum received power (MMP) scheme or maximum received power (MRP) to harvest energy. During the consecutive data transmission phase, UEs choose to receive DL traffic from the same MBSs/SBSs as that associated with during energy harvesting phase, and send UL traffic through the same/another SBS. Leveraging tools from the stochastic geometry, we develop an analytical framework to analyze the average harvested energy and derive expressions for the UL and DL coverage probabilities of the proposed DUDe user association schemes. Our results show that there is an optimal value for the SBS density in the wireless-powered FD HetNets, at which both DL and UL coverage probabilities are maximized. Moreover, by applying MMPA and MRPA scheme, wireless-powered FD HetNets with DUDe achieves up to 138.78%138.78\% and 83.37%83.37\% energy efficiency gain over the FD HetNets with DL/UL coupled user association scheme and without wireless power transfer, respectively

    Double RIS-Assisted MIMO Systems Over Spatially Correlated Rician Fading Channels and Finite Scatterers

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    This paper investigates double RIS-assisted MIMO communication systems over Rician fading channels with finite scatterers, spatial correlation, and the existence of a double-scattering link between the transceiver. First, the statistical information is driven in closed form for the aggregated channels, unveiling various influences of the system and environment on the average channel power gains. Next, we study two active and passive beamforming designs corresponding to two objectives. The first problem maximizes channel capacity by jointly optimizing the active precoding and combining matrices at the transceivers and passive beamforming at the double RISs subject to the transmitting power constraint. In order to tackle the inherently non-convex issue, we propose an efficient alternating optimization algorithm (AO) based on the alternating direction method of multipliers (ADMM). The second problem enhances communication reliability by jointly training the encoder and decoder at the transceivers and the phase shifters at the RISs. Each neural network representing a system entity in an end-to-end learning framework is proposed to minimize the symbol error rate of the detected symbols by controlling the transceiver and the RISs phase shifts. Numerical results verify our analysis and demonstrate the superior improvements of phase shift designs to boost system performance.Comment: 15 pages, 9 figures, accepted by IEEE Transactions on Communication

    A Flexible mmWave Layer 2 Protocol Implementation for Integrated Access and Backhaul Architecture

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    . This work was supported in part by the Spanish Ministry of Science, Innovation and Universities funded by MCIN/AEI/10.13039/501100011033 under Project PID2020-113979RB-C21; and in part by the Ministry of Economic Affairs and Digital Transformation and the European Union-NextGenerationEU under Project TSI-063000-2021-83 (DISRADIO). The work of Randy Verdecia-Peña was supported by the Ministry of Science and Innovation under Contract PRE2018-085032. Publisher Copyright: © 2013 IEEEIn this paper, we present a 3GPP-inspired hardware implementation for the out-of-band Integrated Access and Backhaul (IAB) network, which serves as a solution to both coverage extension and capacity boosting in 5G and beyond networks. By employing an Ettus x310 software-defined radio (SDR) board, Pasternack's 60 GHz Transmitter (Tx) waveguide module, and MatlabTM software, we design and develop an easy-to-use out-of-band mmWave Layer 2 protocol. The proposed protocol decodes a frequency range 1 (FR1) 5G signal as input at 3.5 GHz, which is retransmitted to the UE as a frequency range 2 (FR2) 5G signal at 60 GHz. In the implementation of the Layer 2 protocol, the least squares (LS) estimator is adopted by considering the demodulation reference signal (DM-RS) and the channel state information reference signal (CSI-RS) as pilot symbols in real-world environments. To alleviate the performance degradation in the mmWave access link, a phase noise cancellation (PNC) algorithm based on the phase tracking reference signal (PT-RS) is implemented at the UE node where a PT-RS block structure is introduced in the mmWave Layer 2 protocol transmitter stage. We review and evaluate the key performance indicators (KPIs) of the proposed Layer 2 protocol in real non-line-of-sight (NLOS) environments and a comparison between the gNode-to-UE link is carried out. Our results indicate that the performance of the proposed Layer 2 protocol is similar to the obtained with the off-the-shelf equipment demonstrating the right functionality of the developed algorithms. Experimental results evidence the superiority of the proposed Layer 2 protocol over the gNodeB-to-UE link (direct link communication) and the best performance is obtained when the PNC algorithm is considered in the IAB architecture.publishersversionpublishe

    A survey on reconfigurable intelligent surfaces: wireless communication perspective

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    Using reconfigurable intelligent surfaces (RISs) to improve the coverage and the data rate of future wireless networks is a viable option. These surfaces are constituted of a significant number of passive and nearly passive components that interact with incident signals in a smart way, such as by reflecting them, to increase the wireless system's performance as a result of which the notion of a smart radio environment comes to fruition. In this survey, a study review of RIS-assisted wireless communication is supplied starting with the principles of RIS which include the hardware architecture, the control mechanisms, and the discussions of previously held views about the channel model and pathloss; then the performance analysis considering different performance parameters, analytical approaches and metrics are presented to describe the RIS-assisted wireless network performance improvements. Despite its enormous promise, RIS confronts new hurdles in integrating into wireless networks efficiently due to its passive nature. Consequently, the channel estimation for, both full and nearly passive RIS and the RIS deployments are compared under various wireless communication models and for single and multi-users. Lastly, the challenges and potential future study areas for the RIS aided wireless communication systems are proposed

    Deep Learning Assisted Multiuser MIMO Load Modulated Systems for Enhanced Downlink mmWave Communications

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    This paper is focused on multiuser load modulation arrays (MU-LMAs) which are attractive due to their low system complexity and reduced cost for millimeter wave (mmWave) multi-input multi-output (MIMO) systems. The existing precoding algorithm for downlink MU-LMA relies on a sub-array structured (SAS) transmitter which may suffer from decreased degrees of freedom and complex system configuration. Furthermore, a conventional LMA codebook with codewords uniformly distributed on a hypersphere may not be channel-adaptive and may lead to increased signal detection complexity. In this paper, we conceive an MU-LMA system employing a full-array structured (FAS) transmitter and propose two algorithms accordingly. The proposed FAS-based system addresses the SAS structural problems and can support larger numbers of users. For LMAimposed constant-power downlink precoding, we propose an FASbased normalized block diagonalization (FAS-NBD) algorithm. However, the forced normalization may result in performance degradation. This degradation, together with the aforementioned codebook design problems, is difficult to solve analytically. This motivates us to propose a Deep Learning-enhanced (FAS-DLNBD) algorithm for adaptive codebook design and codebookindependent decoding. It is shown that the proposed algorithms are robust to imperfect knowledge of channel state information and yield excellent error performance. Moreover, the FAS-DLNBD algorithm enables signal detection with low complexity as the number of bits per codeword increases

    Information-Theoretic Study of Time-Domain Energy-Saving Techniques in Radio Access

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    Reduction of wireless network energy consumption is becoming increasingly important to reduce environmental footprint and operational costs. A key concept to achieve it is the use of lean transmission techniques that dynamically (de)activate hardware resources as a function of the load. In this paper, we propose a pioneering information-theoretic study of time-domain energy-saving techniques, relying on a practical hardware power consumption model of sleep and active modes. By minimizing the power consumption under a quality of service constraint (rate, latency), we propose simple yet powerful techniques to allocate power and choose which resources to activate or to put in sleep mode. Power consumption scaling regimes are identified. We show that a ``rush-to-sleep" approach (maximal power in fewest symbols followed by sleep) is only optimal in a high noise regime. It is shown how consumption can be made linear with the load and achieve massive energy reduction (factor of 10) at low-to-medium load. The trade-off between energy efficiency (EE) and spectral efficiency (SE) is also characterized, followed by a multi-user study based on time division multiple access (TDMA)

    Rate-splitting multiple access for non-terrestrial communication and sensing networks

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    Rate-splitting multiple access (RSMA) has emerged as a powerful and flexible non-orthogonal transmission, multiple access (MA) and interference management scheme for future wireless networks. This thesis is concerned with the application of RSMA to non-terrestrial communication and sensing networks. Various scenarios and algorithms are presented and evaluated. First, we investigate a novel multigroup/multibeam multicast beamforming strategy based on RSMA in both terrestrial multigroup multicast and multibeam satellite systems with imperfect channel state information at the transmitter (CSIT). The max-min fairness (MMF)-degree of freedom (DoF) of RSMA is derived and shown to provide gains compared with the conventional strategy. The MMF beamforming optimization problem is formulated and solved using the weighted minimum mean square error (WMMSE) algorithm. Physical layer design and link-level simulations are also investigated. RSMA is demonstrated to be very promising for multigroup multicast and multibeam satellite systems taking into account CSIT uncertainty and practical challenges in multibeam satellite systems. Next, we extend the scope of research from multibeam satellite systems to satellite- terrestrial integrated networks (STINs). Two RSMA-based STIN schemes are investigated, namely the coordinated scheme relying on CSI sharing and the co- operative scheme relying on CSI and data sharing. Joint beamforming algorithms are proposed based on the successive convex approximation (SCA) approach to optimize the beamforming to achieve MMF amongst all users. The effectiveness and robustness of the proposed RSMA schemes for STINs are demonstrated. Finally, we consider RSMA for a multi-antenna integrated sensing and communications (ISAC) system, which simultaneously serves multiple communication users and estimates the parameters of a moving target. Simulation results demonstrate that RSMA is beneficial to both terrestrial and multibeam satellite ISAC systems by evaluating the trade-off between communication MMF rate and sensing Cramer-Rao bound (CRB).Open Acces
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