An Efficient Manifold Algorithm for Constructive Interference Based Constant Envelope Precoding

Liu, Fan; Masouros, Christos; Amadori, Pierluigi Vito; Sun, Hongwei

doi:10.1109/lsp.2017.2748230

Cited by 82 publications

(72 citation statements)

References 24 publications

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“…Let us define the dual variable that associate with the three constraints in (26) as u, v, c respectively, where u i ≥ 0, v i ≥ 0, c m ≥ 0, ∀i, ∀m are the elements of the three dual vectors. The corresponding Lagrangian is given as (27) at the top of the next page. By the following definitions…”

Section: B the Dual Problemmentioning

confidence: 99%

“…Recent works [25], [26] showed that by rotating the destructive interference into constructive region using optimization techniques, the receive SINR target for each user was actually relaxed compared to the conventional SDR-based beamformer, thus a significant power saving was obtained. Given the significant advantage of the interference exploitation technique, it has been already applied to various research fields [27]- [33].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

MIMO Radar and Cellular Coexistence: A Power-Efficient Approach Enabled by Interference Exploitation

Liu

Masouros

et al. 2018

IEEE Trans. Signal Process.

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188

103

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Abstract-We propose a novel approach to enable the coexistence between Multi-Input-Multi-Output (MIMO) radar and downlink multi-user Multi-Input-Single-Output (MU-MISO) communication system. By exploiting the constructive multi-user interference (MUI), the proposed approach trades-off useful MUI power for reducing the transmit power, to obtain a power efficient transmission. This paper focuses on two optimization problems: a) Transmit power minimization at the base station (BS) while guaranteeing the receive signal-to-interference-plus-noise ratio (SINR) level of downlink users and the interference-to-noise ratio (INR) level to radar; b) Minimization of the interference from BS to radar for a given requirement of downlink SINR and transmit power budget. To reduce the computational overhead of the proposed scheme in practice, an algorithm based on gradient projection is designed to solve the power minimization problem. In addition, we investigate the trade-off between the performance of radar and communication, and analytically derive the key metrics for MIMO radar in the presence of the interference from the BS. Finally, a robust power minimization problem is formulated to ensure the effectiveness of the proposed method in the case of imperfect Channel State Information (CSI). Numerical results show that the proposed method achieves a significant power saving compared to conventional approaches, while obtaining a favorable performance-complexity trade-off.

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Section: B the Dual Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

MIMO Radar and Cellular Coexistence: A Power-Efficient Approach Enabled by Interference Exploitation

Liu

Masouros

et al. 2018

IEEE Trans. Signal Process.

Self Cite

188

103

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show abstract

“…Starting from , we can minimize the overall interference (over all UEs k ) . Noting that | g k s k | 2 is a constant, minimizing

\sum_{k} \sum_{i \neq k} false| {boldg}_{k}^{H} s_{i} |^{2}

is equivalent to minimizing

\sum_{k}^{K} \sum_{i}^{K} false| {boldg}_{k}^{H} s_{i} |^{2}

, and the MUI minimization problem can be rewritten as

\begin{matrix} alignleft \\ align-1 & align-2 \min \sum_{i} \sum_{k} {|g_{k}^{H} {bolds}_{i}|}^{2} \\ align-1 & align-2 s.t. ‖ {bolds}_{k} {false‖}_{2}^{2} = P_{k}, \forall k, \end{matrix}

where

\min \sum_{i} \sum_{k} {(||, {boldg}_{k}^{H} s_{i})}^{2} = \min {(‖‖, G^{H} boldS)}_{normalF}^{2}

.…”

Section: Proposed Solutionmentioning

confidence: 99%

“…Starting from (19), we can minimize the overall interference (over all UEs k). [34][35][36] Noting that…”

Section: General Definitionsmentioning

confidence: 99%

Low‐complexity heuristics to beam selection and rate adaptation in sparse massive MIMO systems

Valduga

Deneire

Aparicio-Pardo

et al. 2015

Trans Emerging Tel Tech

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In this work, we propose a novel formulation for a precoder design considering practical rate assignment based on the modulation and coding scheme of the long‐term evolution table, beam selection, and power optimization, which exploits the geometric sparsity of the multiuser massive multiple‐input–multiple‐output channel. We consider two different channel models and provide an optimal solution for the joint beam selection and power optimization as well as a heuristic using Lagrangian relaxation. Assuming knowledge of the beamspace channel, the beamspace precoder consists in selecting and optimizing the power of the beams steered to the user equipments (UEs) in order to maximize the signal‐to‐interference‐plus‐noise ratio at the UE. Furthermore, we propose three additional simple heuristics with low complexity. For these three heuristics, we solve the problem in two steps: (1) selection of beams based on the maximal ratio transmission principle and (2) power allocation per UE. Simulation results show that our optimal solution can achieve a better performance than the zero‐forcing beamforming scheme in the high‐sparsity scenarios. Besides, compared to the linear maximal ratio transmission precoder, the proposed low‐complexity heuristics improve the performance under a scenario with channel sparsity.

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“…All of the above drawbacks make fully-digital processing highly undesirable for a massive MIMO BS. Accordingly, there have been several emerging techniques that aim to reduce the hardware complexity and the power consumption for a massive MIMO BS, including hybrid analog-digital (AD) precoding [15]- [22], constant-envelope (CE) precoding [23]- [26], and low-resolution DACs.…”

mentioning

confidence: 99%

Interference Exploitation 1-Bit Massive MIMO Precoding: A Partial Branch-and-Bound Solution With Near-Optimal Performance

Liu

Masouros

et al. 2020

IEEE Trans. Wireless Commun.

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In this paper, we focus on 1-bit precoding approaches for downlink massive multiple-input multiple-output (MIMO) systems, where we exploit the concept of constructive interference (CI). For both PSK and QAM signaling, we firstly formulate the optimization problem that maximizes the CI effect subject to the requirement of the 1-bit transmit signals. We then mathematically prove that, when employing the CI formulation and relaxing the 1-bit constraint, the majority of the transmit signals already satisfy the 1-bit formulation. Building upon this important observation, we propose a 1-bit precoding approach that further improves the performance of the conventional 1-bit CI precoding via a partial branch-and-bound (P-BB) process, where the BB procedure is performed only for the entries that do not comply with the 1-bit requirement. This operation allows a significant complexity reduction compared to the fully-BB (F-BB) process, and enables the BB framework to be applicable to the complex massive MIMO scenarios. We further develop an alternative 1-bit scheme through an 'Ordered Partial Sequential Update' (OPSU) process that allows an additional complexity reduction. Numerical results show that both proposed 1-bit precoding methods exhibit a significant signal-to-noise ratio (SNR) gain for the error rate performance, especially for higherorder modulations.Index Terms-Massive MIMO, 1-bit precoding, constructive interference, Lagrangian, branch-and-bound. I. INTRODUCTIONM ASSIVE multiple-input multiple-output (MIMO) has become a key enabling technology for the fifthgeneration (5G) and future wireless communication systems [1]-[6]. In the downlink transmission of a massive MIMO system, existing non-linear precoding methods such as Tomlinson-Harashima precoding (THP) [7] or vector perturbation (VP) precoding [8]-[11] are not preferred, due to their prohibitive computational complexity when the number of antennas is large. Instead, it has been shown in [12] that lowcomplexity linear precoding approaches such as zero-forcing (ZF) [13] and regularized ZF (RZF) [14] can achieve nearoptimal performance. Manuscript received XX; revised XX; A. Li, Y. Li and B. Vucetic are with the

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An Efficient Manifold Algorithm for Constructive Interference Based Constant Envelope Precoding

Cited by 82 publications

References 24 publications

MIMO Radar and Cellular Coexistence: A Power-Efficient Approach Enabled by Interference Exploitation

MIMO Radar and Cellular Coexistence: A Power-Efficient Approach Enabled by Interference Exploitation

Low‐complexity heuristics to beam selection and rate adaptation in sparse massive MIMO systems

Interference Exploitation 1-Bit Massive MIMO Precoding: A Partial Branch-and-Bound Solution With Near-Optimal Performance

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