Sum Rate and Fairness Analysis for the MU-MIMO Downlink Under PSK Signalling: Interference Suppression vs Exploitation

Salem, Abdelhamid; Masouros, Christos; Wong, Kai-Kit

doi:10.1109/tcomm.2019.2920645

Cited by 23 publications

(33 citation statements)

References 38 publications

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“…As an initial attempt, [147] conducts performance analysis of CI precoding when PSK signaling is considered, for the first time in the literature, where the achievable rate for each user and the total sum rate upper bound of CI transmission are derived.…”

Section: Fig 3: CI Region Characterization For Psk and Qam Constellamentioning

confidence: 99%

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

Spano

Krivochiza

et al. 2020

IEEE Commun. Surv. Tutorials

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213

127

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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.

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Section: Fig 3: CI Region Characterization For Psk and Qam Constellamentioning

confidence: 99%

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

Spano

Krivochiza

et al. 2020

IEEE Commun. Surv. Tutorials

Self Cite

213

127

View full text Add to dashboard Cite

show abstract

“…Once an end user makes a request for accessing service time, we initialize the procedure for fairness measurement. We introduce the concept of the fairness index from a Multi-User Multiple-Input-Multiple-Output (MU-MIMO) system [25]. The basic idea of the fairness index is balancing between fairness and throughput.…”

Section: ) Calculation Of the Fairness Indexmentioning

confidence: 99%

Dynamic Resource Scheduling Optimization With Network Coding for Multi-User Services in the Internet of Vehicles

et al. 2020

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For Internet of Vehicles (IoV) systems with multiple users, network coding can be introduced to provide efficient error control and throughput improvement services. However, if the heterogeneity characteristics and requirements of the end users (vehicles) are neglected, it will be difficult for an IoV system to provide each end user with fair system services, without which the advantages of network coding cannot be fully achieved and the performance of the multiuser diversity system will be degraded. In this paper, we propose a Dynamic Resource Scheduling Optimization (DRSO) algorithm, a dynamic fair scheduling algorithm combined with network coding for system resource allocation in a multiuser IoV system. We construct a general solution framework for service scheduling: first, we estimate the fairness index for each end user (vehicle) with the key information on Quality of Service (QoS). Second, we construct a service scheduling control model based on the service capability of control entities (multiaccess edge computing servers), and propose a new utility evaluation function. Third, based on the fairness index, we select end users into multiple network coding sets. Network coding sets are the basic units of service scheduling. The optimization objective of the scheduling service is to maximize the total utility of all the network coding sets (the utility of the control entity). Finally, we establish a coding cache queue in the control entity based on the scheduling decision. To obtain the global optimal solution for active queue control, we combine a Quantum Particle Swarm Optimization (QPSO) algorithm with a Proportional Integral (PI) model. Then, the optimal scheduling decision can be made. Extensive simulation results show that DRSO outperforms related scheduling algorithms in varying traffic loads, demonstrating that DRSO can effectively guide service resource allocation. INDEX TERMS multiuser , fairness control, network coding set, cache queue, Internet of Vehicles

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“…where Σ = D [5], [14]. It was shown that, the distribution of Ψ can be approximated to Gamma distribution, Ψ ∼ Γ (ν, θ) [5], [14].…”

Section: A Sep Of the Legitimate Usersmentioning

confidence: 99%

“…where Σ = D [5], [14]. It was shown that, the distribution of Ψ can be approximated to Gamma distribution, Ψ ∼ Γ (ν, θ) [5], [14]. Thus, the received SNR, γ d,k , can be approximated to General Gamma distribution Γ (ρ, ̺, κ) with ρ = 1 2 , ̺ = ν 2 and κ = θ 2 .…”

Section: A Sep Of the Legitimate Usersmentioning

confidence: 99%

See 1 more Smart Citation

Interference Exploitation for Secure Communications: Error Rate and Secrecy Analysis

Salem

Masouros

2020

2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications

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Interference exploitation has recently been shown to provide significant security benefits in multiuser communication systems. In this technique, the known interference is designed to be constructive to the legitimate users and disruptive to the malicious receivers. Accordingly, this paper analyzes the secrecy performance of constructive interference (CI) precoding technique in multiuser multiple-input singleoutput (MU-MISO) systems with phase-shift-keying (PSK) signals and in the presence of multiple passive eavesdroppers. The secrecy performance of CI technique is comprehensively investigated in terms of symbol error probability (SEP), and secrecy sum-rate. Firstly, new and exact analytical expressions for the average SEP of the legitimate users and the eavesdroppers are derived. Departing from classical Gaussian rate analysis, we employ finite constellation rate expressions to investigate the secrecy sum-rate. In this regard, closedform analytical expression of the ergodic secrecy sum-rate is obtained. Then, based on the new secrecy sum-rate expression we revisit adaptive modulation (AM) scheme with the aim to enhance the secrecy performance. The numerical results in this work demonstrate that, the interference exploitation technique achieves a significant performance gain over the interference suppression schemes. Furthermore, the proposed AM scheme provides significant improvement in terms of the secrecy sumrate.

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Sum Rate and Fairness Analysis for the MU-MIMO Downlink Under PSK Signalling: Interference Suppression vs Exploitation

Cited by 23 publications

References 38 publications

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

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

Dynamic Resource Scheduling Optimization With Network Coding for Multi-User Services in the Internet of Vehicles

Interference Exploitation for Secure Communications: Error Rate and Secrecy Analysis

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