scholarly journals Downlink power control and base station assignment

1997 ◽  
Vol 1 (4) ◽  
pp. 102-104 ◽  
Author(s):  
F. Rashid-Farrokhi ◽  
K.J. Ray Liu ◽  
L. Tassiulas
Author(s):  
. Geetanjli

The power control in CDMA systems, grant numerous users to share resources of the system uniformly between each other, leading to expand capacity. With convenient power control, capacity of CDMA system is immense in contrast of frequency division multiple access (FDMA) and time division multiple access (TDMA). If power control is not achieved numerous problems such as the near-far effect will start to monopolize and consequently will reduce the capacity of the CDMA system. However, when the power control in CDMA systems is implemented, it allows numerous users to share resources of the system uniformly between themselves, leading to increased capacity For power control in CDMA system optimization algorithms i.e. genetic algorithm & particle swarm algorithm can be used which regulate a convenient power vector. These power vector or power levels are dogged at the base station and announce to mobile units to alter their transmitting power in accordance to these levels. The performances of the algorithms are inspected through both analysis and computer simulations, and compared with well-known algorithms from the literature.


Author(s):  
Lixin LI ◽  
Yan SUN ◽  
Qianqian CHENG ◽  
Dawei WANG ◽  
Wensheng LIN ◽  
...  

Automatika ◽  
2015 ◽  
Vol 56 (1) ◽  
pp. 84-90 ◽  
Author(s):  
Mladen Mileusnić ◽  
Miroslav Popović ◽  
Aleksandar Lebl ◽  
Dragan Mitić ◽  
Žarko Markov
Keyword(s):  

Algorithms ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 93 ◽  
Author(s):  
Na Su ◽  
Qi Zhu

This paper assumes that multiple device-to-device (D2D) users can reuse the same uplink channel and base station (BS) supplies power to D2D transmitters by means of wireless energy transmission; the optimization problem aims at maximizing the total capacity of D2D users, and proposes a power control and channel allocation algorithm for the energy harvesting D2D communications underlaying the cellular network. This algorithm firstly uses a heuristic dynamic clustering method to cluster D2D users and those in the same cluster can share the same channel. Then, D2D users in the same cluster are modeled as a non-cooperative game, the expressions of D2D users’ transmission power and energy harvesting time are derived by using the Karush–Kuhn–Tucker (KKT) condition, and the optimal transmission power and energy harvesting time are allocated to D2D users by the joint iteration optimization method. Finally, we use the Kuhn–Munkres (KM) algorithm to achieve the optimal matching between D2D clusters and cellular channel to maximize the total capacity of D2D users. Simulation results show that the proposed algorithm can effectively improve the system performance.


Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5307 ◽  
Author(s):  
Shuang Zhang ◽  
Guixia Kang

To support a vast number of devices with less energy consumption, we propose a new user association and power control scheme for machine to machine enabled heterogeneous networks with non-orthogonal multiple access (NOMA), where a mobile user (MU) acting as a machine-type communication gateway can decode and forward both the information of machine-type communication devices and its own data to the base station (BS) directly. MU association and power control are jointly considered in the formulated as optimization problem for energy efficiency (EE) maximization under the constraints of minimum data rate requirements of MUs. A many-to-one MU association matching algorithm is firstly proposed based on the theory of matching game. By taking swap matching operations among MUs, BSs, and sub-channels, the original problem can be solved by dealing with the EE maximization for each sub-channel. Then, two power control algorithms are proposed, where the tools of sequential optimization, fractional programming, and exhaustive search have been employed. Simulation results are provided to demonstrate the optimality properties of our algorithms under different parameter settings.


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