Concavity Approximation Based Power Allocation in Millimeter-Wave MIMO Systems

Hu, Anzhong; Pan, Peng

doi:10.1109/access.2017.2773491

Cited by 3 publications

(1 citation statement)

References 32 publications

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“…The research in [7] proposes a power allocation method based on the maximum and minimum fairness criteria under massive MIMO systems, which maximizes the worst signal-to-noise ratio of all users and ensures the average performance for the users but does not consider the type of service and does not meet the QoS requirements of the users. The research conducted in [8] studies the power allocation problem of massive MIMO systems and proposes a power allocation method using the asymptotic concave formation of the system sum rate, and the sum rate of the system increases with the increased number of antennas but ignores the index of spectral efficiency. The research in [9] proposes a beam allocation and power optimization scheme, which is solved by expressing the problem of beam allocation and power optimization as a multivariate mixed integer nonlinear programming problem.…”

Section: Introductionmentioning

confidence: 99%

Joint Optimization of Massive MIMO System Resources Based on Service QoS

Liu

2023

Electronics

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Aiming at the problem of low throughput and energy efficiency caused by the mutual restriction of energy efficiency and spectral efficiency in massive MIMO systems and the fact that resource allocation does not consider the factors of user service QoS and the upper and lower speed limits, a resource joint optimization method based on user service QoS guarantee is proposed. The method first performs user scheduling according to service delay and channel state under the condition of equal power distribution and calculates the current system capacity, and then combines transmit antenna power and service QoS constraints to redistribute power, and corrects the system capacity, establishing the objective function for the joint optimization of the spectral efficiency and energy efficiency. An algorithm combining deep learning and Q learning is used to solve the problem, and finally, the purpose of joint optimization is achieved. The simulation shows that the joint optimization method proposed in this paper can control the timeout of user data packets more finely and, at the same time, obtain greater energy efficiency and throughput.

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Section: Introductionmentioning

confidence: 99%

Joint Optimization of Massive MIMO System Resources Based on Service QoS

Liu

2023

Electronics

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Dynamic Power Allocation for Cooperative Multi- Antenna Networks in Presence of Mutual Coupling

Ufiteyezu

2021

2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS)

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Design and Performance Analysis of Omnidirectional Space-Time Block Code in Massive MIMO Systems

曹¹

2018

HJWC

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Common signals should be transmitted omnidirectionally to guarantee cell-wide coverage in massive MIMO systems under celluar communication units. Space-Time Block Code (STBC) has received widespread application in MIMO systems, in this paper, we focus on the omnidirectional STBC in massive MIMO downlink, which provides a new thinking for reducing the burden of downlink pilot overhead. We firstly design an omnidirectional precoding (OP) matrix for 2*2 Alamouti Code, which guarantees equal receiving power for user terminals in all spatial directions at any instant time as well as equal instantaneous power for each transmitting antenna. To obtain diversity order of four, OP matrices utilizing $4*4$ STBC and OSTBC Code are also proposed, respectively. What's more, the condition of OP matrices is rewritten considering constant angle domain, and several examples of OP matrices are proposed. We analyse the system performance utilizing omnidirectional STBC in four aspects: bit error rate, peak-to-average ratio (PAPR), channel capacity and outage probability. Simulation results show that one proposed design can 1) reduce bit error bit; 2) maximize channel capacity; 3) preserve the PAPR of transmitted signals.

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Concavity Approximation Based Power Allocation in Millimeter-Wave MIMO Systems

Cited by 3 publications

References 32 publications

Joint Optimization of Massive MIMO System Resources Based on Service QoS

Joint Optimization of Massive MIMO System Resources Based on Service QoS

Dynamic Power Allocation for Cooperative Multi- Antenna Networks in Presence of Mutual Coupling

Design and Performance Analysis of Omnidirectional Space-Time Block Code in Massive MIMO Systems

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