Energy Efficient Symbol-Level Precoding in Multiuser MISO Channels

This paper investigates the idea of exploiting interference among the simultaneous multiuser transmissions in the downlink of multiple antennas systems. Using symbol level precoding, a new approach towards addressing the multiuser interference is discussed through jointly utilizing the channel state information (CSI) and data information (DI). In this direction, the interference among the data streams is transformed under certain conditions to useful signal that can improve the signal to interference noise ratio (SINR) of the downlink transmissions. In this context, new constructive interference precoding techniques that tackle the transmit power minimization (min power) with individual SINR constraints at each user's receivers are proposed. Furthermore, we investigate the CI precoding design under the assumption that the received MPSK symbol can reside in a relaxed region in order to be correctly detected.Comment: 5 pages, 3 figures, to appear in SPAWC 2015. arXiv admin note: substantial text overlap with arXiv:1504.06749, arXiv:1408.470

Practical Interference Exploitation Precoding without Symbol-by-Symbol Optimization: A Block-Level Approach

In this paper, we propose a constructive interference (CI)-based block-level precoding (CI-BLP) approach for the downlink of a multi-user multiple-input single-output (MU-MISO) communication system. Contrary to existing CI precoding approaches which have to be designed on a symbol-by-symbol level, here a constant precoding matrix is applied to a block of symbol slots within a channel coherence interval, thus significantly reducing the computational costs over traditional CI-based symbol-level precoding (CI-SLP) as the CI-BLP optimization problem only needs to be solved once per block. For both PSK and QAM modulation, we formulate an optimization problem to maximize the minimum CI effect over the block subject to a block- rather than symbol-level power budget. We mathematically derive the optimal precoding matrix for CI-BLP as a function of the Lagrange multipliers in closed form. By formulating the dual problem, the original CI-BLP optimization problem is further shown to be equivalent to a quadratic programming (QP) optimization. Numerical results validate our derivations, and show that the proposed CI-BLP scheme achieves improved performance over the traditional CI-SLP method, thanks to the relaxed power constraint over the considered block of symbol slots

Symbol-level Precoding for the Non-linear Multiuser MISO Downlink Channel

This paper investigates the problem of the interference among multiple simultaneous transmissions in the downlink channel of a multi-antenna wireless system. A symbol-level precoding scheme is considered, in order to exploit the multi-user interference and transform it into useful power at the receiver side, through a joint utilization of the data information and the channel state information. In this context, this paper presents novel strategies which exploit the potential of symbol-level precoding to control the per-antenna instantaneous transmit power. In particular, the power peaks amongst the transmitting antennas and the instantaneous power imbalances across the different transmitted streams are minimized. These objectives are particularly relevant with respect to the non-linear amplitude and phase distortions induced by the per-antenna amplifiers, which are important sources of performance degradation in practical systems. More specifically, this work proposes two different symbol-level precoding approaches. A first approach performs a weighted per-antenna power minimization, under Quality-of-Service constraints and under a lower bound constraint on the per-antenna transmit power. A second strategy performs a minimization of the spatial peak-to-average power ratio, evaluated amongst the transmitting antennas. Numerical results are presented in a comparative fashion to show the effectiveness of the proposed techniques, which outperform the state of the art symbol-level precoding schemes in terms of spatial peak-to-average power ratio, spatial dynamic range, and symbol-error-rate over non-linear channels

Intelligent Reflecting Surface based Passive Information Transmission: A Symbol-Level Precoding Approach

Intelligent reflecting surfaces (IRS) have been proposed as a revolutionary technology owing to its capability of adaptively reconfiguring the propagation environment in a cost-effective and hardware-efficient fashion. While the application of IRS as a passive reflector to enhance the performance of wireless communications has been widely investigated in the literature, using IRS as a passive transmitter recently is emerging as a new concept and attracting steadily growing interest. In this paper, we propose two novel IRS-based passive information transmission systems using advanced symbol-level precoding. One is a standalone passive information transmission system, where the IRS operates as a passive transmitter serving multiple receivers by adjusting its elements to reflect unmodulated carrier signals. The other is a joint passive reflection and information transmission system, where the IRS not only enhances transmissions for multiple primary information receivers (PIRs) by passive reflection, but also simultaneously delivers additional information to a secondary information receiver (SIR) by embedding its information into the primary signals at the symbol level. Two typical optimization problems, i.e., power minimization and quality-of-service (QoS) balancing, are investigated for the proposed IRS-based passive information transmission systems. Simulation results demonstrate the feasibility of IRS-based passive information transmission and the effectiveness of our proposed algorithms, as compared to other benchmark schemes.Comment: 14 pages, 11 figures, major revisio

Peak Power Minimization in Symbol-level Precoding for Cognitive MISO Downlink Channels

This paper proposes a new symbol-level precoding scheme at the cognitive transmitter that jointly utilizes the data and channel information to reduce the effect of nonlinear amplifiers, by reducing the maximum antenna power under quality of service constraint at the cognitive receivers. In practice, each transmit antenna has a separate amplifier with individual characteristics. In the proposed approach, the precoding design is optimized in order to control the instantaneous power transmitted by the antennas, and more specifically to limit the power peaks, while guaranteeing some specific target signal-to-noise ratios at the receivers and respecting the interference temperature constraint imposed by the primary system. Numerical results show the effectiveness of the proposed scheme, which outperforms the existing state of the art techniques in terms of reduction of the power peaks

Interference Exploitation-based Hybrid Precoding with Robustness Against Phase Errors

Hybrid analog-digital precoding significantly reduces the hardware costs in massive MIMO transceivers when compared to fully-digital precoding at the expense of increased transmit power. In order to mitigate the above shortfall, we use the concept of constructive interference-based precoding, which has been shown to offer significant transmit power savings when compared with the conventional interference suppression-based precoding in fully-digital multiuser MIMO systems. Moreover, in order to circumvent the potential quality-of-service degradation at the users due to the hardware impairments in the transmitters, we judiciously incorporate robustness against such vulnerabilities in the precoder design. Since the undertaken constructive interference-based robust hybrid precoding problem is nonconvex with infinite constraints and thus difficult to solve optimally, we decompose the problem into two subtasks, namely, analog precoding and digital precoding. In this paper, we propose an algorithm to compute the optimal constructive interference-based robust digital precoders. Furthermore, we devise a scheme to facilitate the implementation of the proposed algorithm in a low-complexity and distributed manner. We also discuss block-level analog precoding techniques. Simulation results demonstrate the superiority of the proposed algorithm and its implementation scheme over the state-of-the-art methods

NOMA Made Practical: Removing the SIC through Constructive Interference

In this paper a novel constructive multiple access (CoMA) scheme is proposed. The new CoMA technique aligns the superimposed signals to the users constructively to the signal of interest. Accordingly, there is no need to remove it at the receiver using successive interference cancellation (SIC) technique. In this regard, optimal CoMA precoders are designed for user paring NOMA multiple-input-single-output (MISO) systems. The results in this paper show that CoMA is an attractive solution for NOMA systems with low number of antennas, and transmission power

STAR-RIS-Enabled Secure Dual-Functional Radar-Communications: Joint Waveform and Reflective Beamforming Optimization

Considering a simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS)-aided dual-functional radar-communications (DFRC) system, this paper proposes a symbol-level precoding-based scheme for concurrent securing confidential information transmission and performing target sensing, where the public signals intended for multiple unclassified users are exploited to deceive the multiple potential malicious radar targets. Specifically, the STAR-RIS-aided DFRC system design is formulated as a joint optimization problem that determines the transmission waveform signal, the transmission and reflection coefficients of STAR-RIS. The objective is to maximize the average received radar sensing power subject to the quality-of-service constraints for multiple communication users, the security constraint for multiple potential eavesdroppers, as well as various practical waveform design restrictions. However, the formulated problem is challenging to handle due to its nonconvexity. Furthermore, the high dimensionality of the optimization variables also renders existing optimization algorithms inefficient. To address these issues, we propose a distance-majorization induced low-complexity algorithm to obtain an efficient solution, which converts the nonconvex joint design problem into a sequence of subproblems that can be solved in closed-form, relieving the required high computational burden of the conventional approaches, e.g., the interior point method. Simulation results confirm the effectiveness of the STAR-RIS in improving the DFRC performance. Besides, by comparing with the state-of-the-art alternating direction method of multipliers (ADMM) algorithm, simulation results validate the efficiency of our proposed optimization algorithm and show that it enjoys excellent scalability for different number of T-R elements equipped at the STAR-RIS