Limited Rate Feedback for Two-User MISO Gaussian Interference Channel With and Without Secrecy

Xu, Yang; Swindlehurst, A. Lee

doi:10.1109/tsp.2018.2855641

Cited by 4 publications

(2 citation statements)

References 49 publications

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“…In the final example, we study the allocation of the quantization bits on the system performance [51]. In particular, in Fig.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…They further demonstrate the ability of the proposed methods to improve the performance of both the primary and cognitive networks. Furthermore, inspired by the results of [51], we study the problem of allocating bits to the CSI of the PBS to the PUs and CUs, and demonstrate that the bit allocation strategy in our robust SLP algorithm is not as important as that in the nonrobust methods. Note that a subset of the results presented in this paper were previously reported in [52].…”

Section: Introductionmentioning

confidence: 99%

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Robust Symbol Level Precoding for Overlay Cognitive Radio Networks

Liu

Masouros

Swindlehurst

2024

IEEE Trans. Wireless Commun.

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This paper focuses on designing robust symbol-level precoding (SLP) in an overlay cognitive radio (CR) network, where the primary and secondary networks transmit signals concurrently. When the primary base station (PBS) shares data and perfect channel state information (CSI) with the cognitive base station (CBS), we derive an SLP approach that minimizes the CR transmission power and satisfies symbol-wise Safety Margin (SM) constraints of both primary users (PUs) and cognitive users (CUs). The resulting optimization has a quadratic objective and linear inequality (LI) constraints, which can be solved by standard convex methods. For the case of imperfect CSI from the PBS, we propose robust SLP schemes. First, with a norm-bounded CSI error model to approximate the uncertain channels, we adopt a max-min philosophy to conservatively achieve robust SLP constraints. Second, we use the additive quantization noise model (AQNM) to describe the quantized PBS CSI and employ a stochastic constraint to formulate the problem. Both robust approaches also result in a quadratic objective with LI constraints. Simulation results show that, rather than simply trying to eliminate the network's cross-interference, the proposed robust SLP schemes enable the primary and secondary networks to aid each other in meeting their quality of service constraints.

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“…In the final example, we study the allocation of the quantization bits on the system performance [51]. In particular, in Fig.…”

Section: Numerical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%