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

2021 ◽  
Author(s):  
Abdolrasoul Sakhaei Gharagezlou ◽  
Jafar Pourrostam ◽  
Mahdi Nangir
Keyword(s):  
Cell Division ◽  
Power Allocation ◽  
Energy Efficient ◽  
Multiple Input Multiple Output ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Efficient Power

scholarly journals Efficient Power Allocation for LDPC-Coded MIMO Systems

2011 ◽  
pp. 127-133
Author(s):  
Layak Ali Sd ◽  
K. Kishan Rao ◽  
M. Sushanth Bab
Keyword(s):  
Interference Cancellation ◽  
Communication Systems ◽  
Mimo Systems ◽  
Geometric Mean ◽  
Multiple Input Multiple Output ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Coded Systems ◽  
Efficient Power ◽  
Q Function

In this papers an efficient ordering scheme for an ordered successive interference cancellation detector is determined under the bit error rate minimization criterion for multiple-input multiple-output(MIMO) communication systems using transmission power control. From the convexity of the Q-function, we evaluate the choice of suitable quantization characteristics for both the decoder messages and the received samples in Low Density Parity Check (LDPC)-coded systems using M-QAM schemes. We derive the ordering strategy that makes the channel gains converge to their geometric mean. Based on this approach, the fixed ordering algorithm is first designed, for which the geometric mean is used for a constant threshold using correlation among ordering results.

scholarly journals Energy Efficiency Optimization for Massive MIMO Non-Orthogonal Unicast and Multicast Transmission with Statistical CSI

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 857 ◽  
Author(s):  
Wang ◽  
Huang ◽  
You ◽  
Xiong ◽  
Li ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Maximization Problem ◽  
Multicast Transmission ◽  
Deterministic Equivalent ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Vector Valued

We study the energy efficiency (EE) optimization problem in non-orthogonal unicast and multicast transmission for massive multiple-input multiple-output (MIMO) systems with statistical channel state information of all receivers available at the transmitter. Firstly, we formulate the EE maximization problem. We reduce the number of variables to be solved and simplify this large-dimensional-matrix-valued problem into a real-vector-valued problem. Next, we lower the computational complexity significantly by replacing the objective with its deterministic equivalent to avoid the high-complex expectation operation. With guaranteed convergence, we propose an iterative algorithm on beam domain power allocation using the minorize maximize algorithm and Dinkelbach’s transform and derive the locally optimal power allocation strategy to achieve the optimal EE. Finally, we illustrate the significant EE performance gain of our EE maximization algorithm compared with the conventional approach through conducting numerical simulations.

Transceiver Optimization for ToA-Based Localization of Mobile WSN

2016 ◽  
Vol 25 (09) ◽  
pp. 1650100 ◽  
Author(s):  
Mostafa Taheri ◽  
Seyed Ahmad Motamedi
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Multiple Input Multiple Output ◽  
Sensor Nodes ◽  
Mobile Nodes ◽  
Accurate Localization ◽  
Optimum Selection ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Localization Precision

One of the main parameters in wireless sensor networks (WSNs) is the design of energy-efficient protocols. And accuracy is another central goal of localization. Since sensor nodes run on battery power, any WSN application and accurate localization needs to be energy-efficient. In this paper, the accuracy of localization is increased by accurate measurement of the distance between the mobile sensors. Limit error in multiple-input multiple-output (MIMO) has been calculated by CRB method. Virtual MIMO (VMIMO) technique can obtain better localization precision and the localization is energy-efficient. Optimum selection of the number of the transceiver nodes is obtained by the lowest possible energy consumption, the existent localization error, and speed of nodes. Mathematical relation between energy consumption and localization of mobile nodes is presented and then verified by simulation. VMIMO decreases power of transmitters and this in turn will result in decreasing destructive effects of electromagnetic sensitivity (EMS) on body. Furthermore, optimized localization parameters will increase the efficiency of the system and network lifetime.

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