Optimal power allocation for massive MU-MIMO downlink TDD systems

Saatlou, O.; Ahmad, M. Omair; Swamy, M.N.S.

doi:10.1109/ccece.2016.7726729

Cited by 8 publications

(4 citation statements)

References 14 publications

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“…According to Lemma 4 and Proposition 4, the optimization problem given by (38) can be rewritten as [42] max…”

Section: A Maximum-ratio Transmissionmentioning

confidence: 99%

“…A method of power control among the users in conjunction with the BT method has been proposed in [41] based on the waterfilling approach to maximize SE. In [42], a power control scheme between the data and pilot symbols has been proposed in order to improve SE, where the BT scheme is employed. In [43], a method of power allocation among each of the pilot and data symbols of all the users is proposed to maximize SE, where the total power budget per coherence interval for all users is given.…”

Section: Introductionmentioning

confidence: 99%

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Spectral Efficiency Maximization of a Single Cell Massive MU-MIMO Down-Link TDD System by Appropriate Resource Allocation

2019

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This paper deals with the problem of maximizing the spectral efficiency in a massive multi-user MIMO downlink system, where a base station is equipped with a very large number of antennas and serves single-antenna users simultaneously in the same frequency band, and the beamforming training scheme is employed in the time-division duplex mode. An optimal resource allocation that jointly selects the training duration on uplink transmission, the training signal power on downlink transmission, the training signal power on uplink transmission, and the data signal power on downlink transmission is proposed in such a way that the spectral efficiency is maximized given the total energy budget. Since the spectral efficiency is the main concern of this work, and its calculation using the lower bound on the achievable rate is computationally very intensive, in this paper, we also derive approximate expressions for the lower bound of achievable downlink rate for the maximum ratio transmission (MRT) and zero-forcing (ZF) precoders. The computational simplicity and accuracy of the approximate expressions for the lower bound of achievable downlink rate are validated through simulations. By employing these approximate expressions, experiments are conducted to obtain the spectral efficiency of the massive MIMO downlink time-division duplexing system with the optimal resource allocation and that of the beamforming training scheme. It is shown that the spectral efficiency of the former system using the optimal resource allocation is superior to that yielded by the latter scheme in the cases of both MRT and ZF precoders.

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“…According to Lemma 4 and Proposition 4, the optimization problem given by (38) can be rewritten as [42] max…”

Section: A Maximum-ratio Transmissionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spectral Efficiency Maximization of a Single Cell Massive MU-MIMO Down-Link TDD System by Appropriate Resource Allocation

2019

Self Cite

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“…In this model, it is assumed that users have enough information about the channel status to decode data signals. A reciprocal channel between uplink and downlink is considered in duplex time division mode 3 …”

Section: Introductionmentioning

confidence: 99%

“…A reciprocal channel between uplink and downlink is considered in duplex time division mode. 3 A modified power allocation (PA) scheme is proposed to increase the EE and capacity of the massive MIMO system in. 4 In the proposed scheme, first, channels of the telecommunication system are divided into a number of equivalent subchannels by using special values.…”

Section: Introductionmentioning

confidence: 99%

Secure energy efficient power allocation in massive multiple‐input multiple‐output systems with an eavesdropper using cell division technique

Gharagezlou

Pourrostam

Nangir

2021

Int J Communication

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Summary In this paper, we study energy‐efficient power allocation (PA) to secure the confidential information of massive multiple‐input multiple‐output (MIMO) systems in the presence of an eavesdropper. First a training scheme is presented in the uplink using the MMSE method. Based on the estimated channel state information (CSI), the base station (BS) encrypts the confidential information. Next, the ergodic secret rate is obtained at the downlink. In this paper, in order to maximize the ergodic secrecy rate, the allocation of common power in the uplink and downlink is proposed by considering the constraints such as the transmit power constraint in the uplink, the transmit power constraint in the downlink, and the minimum ergodic secret rate constraint. The objective function in the proposed scenario is a nonconvex problem, which first becomes a convex problem and then, by using the Lagrange dual function method, the problem becomes an unconstraint problem. We also divide the cell into two areas using the cell division method. A practical energy‐efficient PA algorithm is presented which deals with the adverse effect of the eavesdropper. Simulations are carried out to demonstrate the effectiveness of the proposed methods.

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