Max-Min Beamforming Design for Heterogeneous Networks With Hardware Impairments

Xu, Yongjun; Xie, Hao; Hu, Rose Qingyang

doi:10.1109/lcomm.2020.3044936

Cited by 14 publications

(7 citation statements)

References 16 publications

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“…represents the random transceiver hardware impairments at the k-th IoT device and the AP during t k [30], [37], respectively. Hence, the amount of offloaded computation bits by the k-th IoT device is given by…”

Section: B Local Computingmentioning

confidence: 99%

“…Introducing ( 39) into (37), and considering the variable substitution E k = P k t k , ∀k ∈ K, we can obtain the optimal solution of ( 37) by iteratively solving the following convex problem maximize…”

Section: Computation Bits Maximization For Irs-assisted Mec With Phas...mentioning

confidence: 99%

“…The procedure for solving the transmit power and time allocation problem (37) is illustrated in Algorithm 3.…”

Section: Computation Bits Maximization For Irs-assisted Mec With Phas...mentioning

confidence: 99%

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Computation Bits Maximization for IRS-Aided Mobile-Edge Computing Networks With Phase Errors and Transceiver Hardware Impairments

Mao,

Zhang,

et al. 2024

IEEE Trans. Veh. Technol.

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Intelligent reflecting surface (IRS) is a hopeful technique to improve the computation offloading efficiency for mobile-edge computing (MEC) networks. However, the phase errors (PEs) of IRS and transceiver hardware impairments (THIs) will greatly degrade the performance of IRS-assisted MEC networks. To overcome this bottleneck, this paper first investigates the computation bits maximization problem for IRSassisted MEC networks with PEs, where multiple Internet of Things (IoT) devices can offload their computation tasks to access points with the aid of IRS. By exploiting the block coordinate descent method, we design a multi-block optimization algorithm to tackle the non-convex problem. In particular, the optimal IRS phase shift, time allocation, transmit power and local computing frequencies of IoT devices are derived in closed-form expressions. Moreover, we further study the joint impact of PEs and THIs on the total computation bits of considered systems, where same methods in the scenario with PEs are used to obtain the optimal IRS phase shift and local computing frequencies of IoT devices, while an approximation algorithm and the variable substitution method are used to acquire the optimal transmit power and time allocation strategy. Finally, numerical results validate that our proposed methods can significantly outperform benchmark methods in terms of total computation bits.

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Section: B Local Computingmentioning

confidence: 99%

Section: Computation Bits Maximization For Irs-assisted Mec With Phas...mentioning

confidence: 99%

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Computation Bits Maximization for IRS-Aided Mobile-Edge Computing Networks With Phase Errors and Transceiver Hardware Impairments

Mao,

Zhang,

et al. 2024

IEEE Trans. Veh. Technol.

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“…Recently, work done in [18] provided the detailed survey on resource allocation in 5G HCNs with an explanation of existing literature, future trends, and possible challenges. The authors in [19] proposed a heterogeneous network scheme that guaranteed the QoS and fairness of all users while minimizing the interference. Similarly, the work proposed in [20] investigated the resource allocation scheme in heterogeneous networks considering the system robustness and interference efficiency.…”

Section: Related Workmentioning

confidence: 99%

Efficient Resource Allocation Using Distributed Edge Computing in D2D Based 5G-HCN With Network Slicing

Nadeem¹,

Amin

Loo

et al. 2021

IEEE Access

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Fifth Generation (5G) cellular networks aim to overcome the pressing demands posed by dynamic Quality of Service (QoS) constraints, which have primarily remained unaddressed using conventional network infrastructure. Cellular networks of the future necessitate the formulation of efficient resource allocation schemes that readily meet throughput requirements. The idea of combining Device-to-Device (D2D), Mobile Edge Computing (MEC), and Network slicing (NS) can improve spectrum utilization with better performance and scalability. This work presents a spectrum efficiency optimization problem in D2D based 5G-Heterogeneous Cellular Network (5G-HCN) with NS. Owing to the shortage of resources, we propose an underlay model where macro-cell users (MUs), small-cell users (SUs), and D2D users (DUs) reuse the resources while considering the effects of interference. The goal is to maximize the average network spectrum efficiency (SE) and throughput without degrading the system performance. The problem at hand is naturally a non-convex mixed-integer non-linear programming (MINLP) problem that is intractable. Therefore, we have suggested a distributed resource allocation strategy with an edge computing (DRA-EC) approach to find the sub-optimal solution. In distributed augmented Lagrange method, each edge router located at BS will solve its problem locally, and the consensus algorithm will find the global solution using these local estimates. The central slice controller will cut the customized network slices according to the bandwidth requirements of each user type with optimized spectrum information. The simulation outcomes prove that our proposed method is near the central optimization scheme with low computational complexity. It is much better because it reduces the computational time and system overhead.

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“…Besides its ability to improve the system performance dramatically, IRS offers some other advantages as compared to the traditional active counterparts such as multiple-input-multiple-output (MIMO) and relays. 15 These advantages are: (i) IRS is nearly passive in nature which implies that it does not require power-hungry radio frequency (RF) chains for its operation; (ii) IRS is spectral efficient as it operates in full-duplex mode; (iii) IRS is free of antenna amplification noise; and (iv) IRS is transparent in nature, thus can readily be integrated with other emerging wireless system technologies (eg, heterogeneous networks, 16 non-orthogonal multiple access (NOMA) and backscatter, 17 etc.) without requiring any complex modifications.…”

Section: Introductionmentioning

confidence: 99%

Performance analysis for IRS‐aided communication systems with composite fading/shadowing direct link and discrete phase shifts

Waqar

2021

Trans Emerging Tel Tech

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Intelligent reflecting surface (IRS) is an emerging technology and serves as a key component of any smart radio environment. In this article, we consider an IRS that assists communication of a direct link between a single-antenna transmitter and a receiver. It is assumed that a direct link experiences composite fading/shadowing and is modeled by Generalized-K distribution. Moreover, IRS has line-of-sight (LoS) paths, therefore, Rician distribution is used to characterize the fading for these paths. We also consider phase errors that exist due to discrete number of phase shifts. We derive an approximation for the end-to-end signal-to-noise ratio (SNR) which shows that an amplitude of the direct link is increased by a positive offset because of the presence of IRS. Based on this SNR approximation, a new statistical framework that includes cumulative distribution function (CDF), probability density function (PDF), and moment generating function (MGF) is developed. Leveraging this statistical framework, we derive new and accurate closed-form approximations for the outage probability, average error probability, ergodic capacity and generalized moments. It is shown that the considered IRS-aided system (IAS) achieves much better performance even with a few numbers of phase shifts as compared to other baseline systems. Simulations are also provided which verify the tightness of our derived approximations.

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Max-Min Beamforming Design for Heterogeneous Networks With Hardware Impairments

Cited by 14 publications

References 16 publications

Computation Bits Maximization for IRS-Aided Mobile-Edge Computing Networks With Phase Errors and Transceiver Hardware Impairments

Computation Bits Maximization for IRS-Aided Mobile-Edge Computing Networks With Phase Errors and Transceiver Hardware Impairments

Efficient Resource Allocation Using Distributed Edge Computing in D2D Based 5G-HCN With Network Slicing

Performance analysis for IRS‐aided communication systems with composite fading/shadowing direct link and discrete phase shifts

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