Comparison of the MRT and ZF Precoding in Massive MIMO Systems from Energy Efficiency Viewpoint

Nangir, Mahdi; Gharagezlou, Abdolrasoul Sakhaei; Imani, Nima

doi:10.1109/icee55646.2022.9827366

Cited by 9 publications

(7 citation statements)

References 11 publications

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“…Table 1 provides values of them which are used in the simulation process. These values are inspired by [21][22][23][24][25][26]. Figure 2 shows how the secure EE changes by increasing the peak transmission power.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

Optimizing secure power allocation in massive MIMO systems with an eavesdropper under imperfect CSI conditions

Gharagezlou,

Nangir,

Imani

2024

IET Communications

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This paper discusses the operation of a massive multiple‐input multiple‐output (MIMO) system from a different perspective. The system is performed in the presence of an eavesdropper who is trying to disrupt the message being transmitted between the base station (BS) and the users. An attempt has been made to maximize the secure energy efficiency (EE) of the system by allocating appropriate power to each user. The channel state information (CSI) between users and the BS is considered imperfect and the employed precoding scheme is the zero forcing (ZF). The CSI related to the eavesdropper is considered to be perfect and its precoding is assumed to be the maximum ratio transmission (MRT). The problem of optimization that is for maximizing the EE has two constraints including the maximum transmission power and the minimum user data rate. To improve the performance of system, the cell division technique is applied, which results in approaching the performance of system to the without eavesdropper scenario. Five various scenarios have been investigated in this research, and it is proved that the proposed method improves the system performance in all cases. The numerical and simulation results obtained from implementation of the proposed algorithm confirm the claim.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Optimizing secure power allocation in massive MIMO systems with an eavesdropper under imperfect CSI conditions

Gharagezlou,

Nangir,

Imani

2024

IET Communications

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“…The values of them and some other used parameters in the simulation process are given in Table 2, which are inspired by previous works. 20,21 Figure 2 shows how the EE varies with increasing the value of maximum transmission power. As the maximum transmission power increases, so does the EE.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…These types of algorithms works based on the initial value of these parameters. The values of them and some other used parameters in the simulation process are given in Table 2, which are inspired by previous works 20,21 …”

Section: Simulation Results and Discussionmentioning

confidence: 99%

Energy efficient power allocation in MIMO relaying systems with the MRT precoding

Imani

Gharagezlou

Nangir

2023

Int J Communication

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Multiple-input multiple-output (MIMO) systems perform well from the energy efficiency (EE) and the spectral efficiency (SE) points of view in fifth generation (5G) communication systems. This paper considers the operation of a MIMO system with a relay. The optimization problem relates to the EE maximization. This problem has two types of limitations, which provide a maximum transmission power and a minimum data rate for users. The encountered objective function is in a fractional form and thus it is a nonconvex function. Besides, the problem is constrained. We utilize a lower bound analysis for the data rates, some properties of the linear programming, and the maximum ratio transmission (MRT) precoding scheme to obtain a convex objective function. Using the Lagrange dual function, we obliterate the constraints of the problem and then it is easy to solve. To improve system performance, users are divided into two groups based on their channel gains, and the maximum transmission power is reasonably divided between them. Two iterative algorithms are proposed to solve the optimization problem numerically, and finally we investigate performance of the proposed method.

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“…As it can be seen in the relation of EE, it is a fractional and nonlinear function. The nonlinear programming properties and the Hessian matrix is utilized to convert our optimization problem to a convex optimization problem 21,22 . By using the method that is introduced in Kim and Shim, 1 the converted problem can be expounded in the following way:

\max_{({}, p_{1}, p_{2}, …, p_{K})} ({}, {falsefalse}_{\sum}^{i = 1} r_{i} - q^{*} false({falsefalse}_{\sum}^{i = 1} p_{i} + {falsefalse}_{\sum}^{m = 1} P_{c, m} false)) = 0,

where maximum value of the EE is shown by

q^{*}

.…”

Section: The Proposed Scheme and Optimization Problemmentioning

confidence: 99%

“…The nonlinear programming properties and the Hessian matrix is utilized to convert our optimization problem to a convex optimization problem. 21,22 By using the method that is introduced in Kim and Shim, 1 the converted problem can be expounded in the following way:…”

Section: The Proposed Power Allocation Schemementioning

confidence: 99%

An energy‐efficient power allocation scheme for millimeter‐wave MIMO‐NOMA systems

Gharagezlou

Nangir

Liqvan

et al. 2022

Int J Communication

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Summary There are many challenges in fifth generation (5G) telecommunication systems, due to the increasing demands and applications. The most important of which are need to have higher energy efficiency (EE) and spectral efficiency (SE). They are critical in the practical multiple‐input multiple‐output (MIMO) telecommunication systems. Non‐orthogonal multiple access (NOMA) methods and millimeter‐waves can be used in conjunction with MIMO systems to improve their EE and SE performance. In this paper, we investigate the application of NOMA and mm‐Wave transmission in the downlink of MIMO systems. Then, we formulate the optimization problem for users in MIMO‐NOMA systems to maximize the EE that is subject to minimum data rate to satisfy required quality of service (QoS) and maximum transmission power. To achieve the optimal power allocation for users, we reach a problem for the EE maximization that is non‐convex and solution of the optimization problem is not trivial. We exploit a lower bound of the data rate and the Lagrange dual function to convert it to a convex and unconstrained problem, which is easy to solve. In the next step, we derive a relation for determining the optimal power allocation of users. In addition, a numerical algorithm is presented that can be used to solve the problem. According to the simulation results of the proposed algorithm, our method performs better and provides higher EE than both orthogonal multiple access and equal power allocation schemes.

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Comparison of the MRT and ZF Precoding in Massive MIMO Systems from Energy Efficiency Viewpoint

Cited by 9 publications

References 11 publications

Optimizing secure power allocation in massive MIMO systems with an eavesdropper under imperfect CSI conditions

Optimizing secure power allocation in massive MIMO systems with an eavesdropper under imperfect CSI conditions

Energy efficient power allocation in MIMO relaying systems with the MRT precoding

An energy‐efficient power allocation scheme for millimeter‐wave MIMO‐NOMA systems

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