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Block-Level MU-MISO Interference Exploitation Precoding: Optimal Structure and Explicit Duality

delete2024-11-01
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OA
AI
J
Junwen Yang
A
Ang Li *
廖学文 cover
廖学文 (Xuewen Liao) *
C
Christos Masouros
A
A. Lee Swindlehurst
DOI:10.1109/JIOT.2024.3438569delete
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Abstract

Abstract

En 中文
This article investigates block-level interference exploitation (IE) precoding for multiuser multiple-input-single-output (MU-MISO) downlink systems. To overcome the need for symbol-level IE precoding to frequently update the precoding matrix, we propose to jointly optimize all the precoders or transmit signals within a transmission block. The resultant precoders only need to be updated once per block, and while not necessarily constant over all the symbol slots, we refer to the technique as block-level slot-variant IE precoding. Through a careful examination of the optimal structure and the explicit duality inherent in block-level power minimization (PM) and signal-to-interference-plus-noise ratio (SINR) balancing (SB) problems, we discover that the joint optimization can be decomposed into subproblems with smaller variable sizes. As a step further, we propose block-level slot-invariant IE precoding by adding a structural constraint on the slot-variant IE precoding to maintain a constant precoder throughout the block. A novel linear precoder for IE is further presented, and we prove that the proposed slot-variant and slot-invariant IE precoding share an identical solution when the number of symbol slots does not exceed the number of users. Numerical simulations demonstrate that the proposed precoders achieve a significant complexity reduction compared against benchmark schemes, without sacrificing performance.
Keywords:
interference exploitation (IE)
interference management
Block-level precoding
interference exploitation (IE)
power minimization (PM)
power minimization (PM)
signal-to-interference-plus-noise ratio (SINR) balancing (SB)
signal-to-interference-plus-noise ratio (SINR) balancing (SB)
signal-to-interference-plus-noise ratio (SINR) balancing (SB)
multiuser multiple-input- single-output (MU-MISO)
multiuser multiple-input- single-output (MU-MISO)
multiuser multiple-input- single-output (MU-MISO)
multiuser multiple-input- single-output (MU-MISO)
multiuser multiple-input- single-output (MU-MISO)
symbol-level precoding (SLP)
symbol-level precoding (SLP)
signal-to-interference-plus-noise ratio (SINR) balancing (SB)
symbol-level precoding (SLP)

Journal

IEEE Internet of Things Journal cover
IEEE Internet of Things Journal
IF:
8.9
Papers:
1.4W
Citations:
7.8W

Organization

X
xi'an jiaotong university
Scholars:
9.2W
Papers: 6.6W
Citations: 75
U
University College London
Scholars:
7.9W
Papers: 6.2W
Citations: 15.7W
U
university of london
Scholars:
21.5W
Papers: 19.7W
Citations: 305
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