SYMBOL LEVEL PRECODING TECHNIQUES FOR HARDWARE AND POWER EFFICIENT WIRELESS TRANSCEIVERS

Large-scale antennas are crucial for next generation wireless communication systems as they improve spectral efficiency, reliability and coverage compared to the traditional ones that are employing antenna arrays of few elements. However, the large number of antenna elements leads to a big increase in power consumption of conventional fully digital transceivers due to the one Radio Frequency (RF) chain / per antenna element requirement. The RF chains include a number of different components among which are the Digital-to-Analog Converters (DACs)/Analog-to-Digital Converters (ADCs) that their power consumption increases exponential with the resolution they support. Motivated by this, in this thesis, a number of different architectures are proposed with the view to reduce the power consumption and the hardware complexity of the transceiver. In order to optimize the transmission of data through them, corresponding symbol level precoding (SLP) techniques were developed for the proposed architectures. SLP is a technique that mitigates multi-user interference (MUI) by designing the transmitted signals using the Channel State Information and the information-bearing symbols. The cases of both frequency flat and frequency selective channels were considered. First, three different power efficient transmitter designs for transmission over frequency flat channels and their respective SLP schemes are considered. The considered systems tackle the high hardware complexity and power consumption of existing SLP techniques by reducing or completely eliminating fully digital RF chains. The precoding design is formulated as a constrained least squares problem and efficient algorithmic solutions are developed via the Coordinate Descent method. Next, the case of frequency selective channels is considered. To this end, Constant Envelope precoding in a Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing system (CE MIMO-OFDM) is considered. In CE MIMO-OFDM the transmitted signals for each antenna are designed to have constant amplitude regardless of the channel realization and the information symbols that must be conveyed to the users. This facilitates the use of power-efficient components, such as phase shifters and non-linear power amplifiers. The precoding problem is firstly formulated as a least-squares problem with a unit-modulus constraint and solved using an algorithm based on the coordinate descent (CCD) optimization framework and then, after reformulating the problem into an unconstrained non-linear least squares problem, a more computationally efficient solution using the Gauss-Newton algorithm is presented. Then, CE MIMO-OFDM is considered for a system with low resolution DACs. The precoding design problem is formulated as a mixed discrete- continuous least-squares optimization one which is NP-hard. An efficient low complexity solution is developed based also on the CCD optimization framework. Finally, a precoding scheme is presented for OFDM transmission in MIMO systems based on one-bit DACs and ADCs at the transmitter’s and the receiver’s end, respectively, as a way to reduce the total power consumption. The objective of the precoding design is to mitigate the effects of one-bit quantization and the problem is formulated and then is split into two NP hard least squares optimization problems. Algorithmic solutions are developed for the solution of the latter problems, based on the CCD framework

Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions

Interference is traditionally viewed as a performance limiting factor in wireless communication systems, which is to be minimized or mitigated. Nevertheless, a recent line of work has shown that by manipulating the interfering signals such that they add up constructively at the receiver side, known interference can be made beneficial and further improve the system performance in a variety of wireless scenarios, achieved by symbol-level precoding (SLP). This paper aims to provide a tutorial on interference exploitation techniques from the perspective of precoding design in a multi-antenna wireless communication system, by beginning with the classification of constructive interference (CI) and destructive interference (DI). The definition for CI is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed. In addition, the extension of CI precoding to other application scenarios as well as for hardware efficiency is also described. Proof-of-concept testbeds are demonstrated for the potential practical implementation of CI precoding, and finally a list of open problems and practical challenges are presented to inspire and motivate further research directions in this area

Constant Envelope MIMO-OFDM Precoding for Low Complexity Large-Scale Antenna Array Systems

Herein, we consider constant envelope precoding in a multiple-input multiple-output orthogonal frequency division multiplexing system (CE MIMO-OFDM) for frequency selective channels. In CE precoding the signals for each transmit antenna are designed to have constant amplitude regardless of the channel realization and the information symbols that must be conveyed to the users. This facilitates the use of power-efficient components, such as phase shifters (PS) and nonlinear power amplifiers, which are key for the feasibility of large-scale antenna array systems because of their low cost and power consumption. The CE precoding problem is firstly formulated as a least-squares problem with a unit modulus constraint and solved using an algorithm based on coordinate descent. The large number of optimization variables in the case of the MIMO-OFDM system motivates the search for a more computationally efficient solution. To tackle this, we reformulate the CE precoding design into an unconstrained nonlinear least-squares problem, which is solved efficiently using the Gauss-Newton algorithm. Simulation results underline the efficiency of the proposed solutions and show that they outperform state of the art techniques

Joint Symbol Level Precoding and Combining for MIMO-OFDM Transceiver Architectures Based on One-Bit DACs and ADCs

Herein, a precoding scheme is developed for orthogonal frequency division multiplexing (OFDM) transmission in multiple-input multiple-output (MIMO) systems that use one-bit digital-to-analog converters (DACs) and analog-to-digital converters (ADCs) at the transmitter and receiver, respectively, as a means to reduce the power consumption. Two different one-bit architectures are presented. In the first, a single user MIMO system is considered where the DACs and ADCs of the transmitter and the receiver are assumed to be one-bit and in the second, a network of analog phase shifters is added at the receiver as an additional analog-only processing step with the view to mitigate some of the effects of coarse quantization. The precoding design problem is formulated and then split into two NP-hard optimization problems, which are solved by an algorithmic solution based on the Cyclic Coordinate Descent (CCD) framework. The design of the analog post-coding matrix for the second architecture is decoupled from the precoding design and is solved by an algorithm based on the alternating direction method of multipliers (ADMM). Numerical results show that the proposed precoding scheme successfully mitigates the effects of coarse quantization and the proposed systems achieve a performance close to that of systems equipped with full resolution DACs/ADCs

2018 IEEE 23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)

Large-Scale Antenna Array Systems may be used to serve multiple users in the same time-frequency resource block which results to harmful multi-user interference (MUI). In the literature precoding techniques have been proposed as a way to mitigate the induced MUI, by designing the transmitted signals using the knowledge of the Channel State Information (CSI), in block-level precoding (BLP) or both the CSI and the information-bearing symbols, in symbol-level precoding (SLP). However, the proposed SLP techniques require fully digital baseband processing which is infeasible in large-scale antenna array systems because of the high cost and power consumption of radio frequency (RF) components. In order to reduce the number of y-RF chains, we address an Antenna Selection Symbol-Level Precoding (AS-SLP) scheme, which minimizes the MUI by activating only a subset of the available antennas. For this scheme we develop an efficient algorithm, based on Coordinate Descent. Simulations provide an insight on the efficiency of the proposed approach and its improvement with respect to the fully digitally approaches

Non-Orthogonal Multicast and Unicast Robust Beamforming in Integrated Terrestrial-Satellite Networks

This paper studies the non-orthogonal multicast and unicast coordinated beamforming design for integrated terrestrial and satellite networks (ITSN), when the channel state information at the transmitter (CSIT) is imperfect. In order to mitigate the interference induced by simultaneous multicast and unicast links along with the spectrum coexisting mechanism for integrated terrestrial and satellite transmissions, we consider a two-layer layered division multiplexing (LDM) structure where the mul ticast and unicast services are provided in different layers. We formulate a coordinated beamforming problem with the objective to minimize the transmit power under individual quality of service (QoS) constraints. With regard to the unknown convexity of the transmit power minimization problem, we transform the original infeasible optimization into a deterministic optimization form with linear matrix inequality (LMI) by utilizing S-procedure and semi-definite relaxation (SDR) methods. Then, we introduce a penalty function and propose an iterative algorithm with guaranteed convergence to obtain optimal solutions. Simulation results demonstrate the superiority of the proposed coordinated beamforming scheme, especially for the case of imperfect CSIT, while our LDM based coordinated beamforming scheme signifi cantly outperforms the conventional ones in terms of sum rate. Index Terms—Integrated terrestrial and satellite networks (IT SN), beamforming, robust, layered division multiplexing (LDM

Area-Power Analysis of FFT Based Digital Beamforming for GEO, MEO, and LEO Scenarios

Satellite communication systems can provide seamless wireless coverage directly or through complementary ground terrestrial components and are projected to be incorporated into future wireless networks, particularly 5G and beyond networks. Increased capacity and flexibility in telecom satellite payloads based on classic radio frequency technology have traditionally translated into increased power consumption and dissipation. Much of the analog hardware in a satellite communications payload can be replaced with highly integrated digital components that are often smaller, lighter, and less expensive, as well as software reprogrammable. Digital beamforming of thousands of beams simultaneously is not practical due to the limited power available onboard satellite processors. Reduced digital beamforming power consumption would enable the deployment of a full digital payload, resulting in comprehensive user applications. Beamforming can be implemented using matrix multiplication, hybrid methodology, or a discrete Fourier transform (DFT). Implementing DFT via fast Fourier transform (FFT) reduces the power consumption, process time, hardware requirements, and chip area. Therefore, in this paper, area-power efficient FFT architectures for digital beamforming are analyzed. The area in terms of look up tables (LUTs) is estimated and compared among conventional FFT, fully unrolled FFT, and a 4-bit quantized twiddle factor (TF) FFT. Further, for the typical satellite scenarios, area, and power estimation are reported