Novel Adaptive Step Power Control algorithm for 3G WCDMA cellular system

This paper proposes a joint adaptive rate selection and power control algorithm for broadband TDMA/TDM wireless networks. The proposed algorithm is a modified, enhanced, and more robust version of the selective power control with active link protection (SPC-ALP) algorithm proposed for adaptive transmission rate and power control in CDMA networks [R.Jantti and S. Kim, 2000]. Unlike SPC-ALP, the proposed algorithm uses adaptive coding and modulation (instead of variable spreading gain) for transmission rate control. In addition, the proposed algorithm is different in two aspects; the first one is the inclusion of the cochannel interferer assistance mode, while the second one is the use of the signal quality as a criterion for user removal. Results show that the proposed algorithm outperforms SPC-ALP in terms of the net throughput and signal quality measures such as the outage probability and frame error rate. Channel reallocation is also studied and found to be very effective in enhancing the system performance particularly at low to medium loading.

In this paper we study the performance of two Power Control algorithms: the Adaptive Standard Power Control (ASPC) and the Standard Power Control (PCA) algorithms. Simulation of both algorithms is being done under three different network conditions including the case with varying SIR target. In order to achieve robust estimates of the performance we have undertaken Monte-Carlo analysis of 500 runs for each case. These results show that the performance ASPC is be better than PCA under the different network conditions considered in this paper. All simulations are done in MATLAB.

In order to both counteract the near-far problem and maintain a constant average performance to all users in a cellular CDMA system, adaptive power control is essential. In situations where the round trip delay between the mobile and the base station is smaller than the correlation time of the channel (e.g., terrestrial systems, and systems using base stations onboard low altitude UAVs in tactical environments), power control schemes using feedback from the base station can be effective to compensate for the multipath fading. In this paper, we present the performance of such a closed loop power control (CLPC) scheme applied to a cellular CDMA system. The effect of various loop parameters, including power control update rate, loop delay due to propagation and processing, and vehicle speed, on the average bit error performance of the system are estimated through simulation. The capacity improvement due to effective power control in a single cell as well as a multi-cell CDMA system operating over both frequency non-selective and frequency selective fading channels are estimated.

The transmitted data rate over the forward traffic channel in the existing CDMA cellular communication system and the proposed next generation CDMA cellular communication systems is variable from frame to frame. In order to reduce the frame overhead, however, the data rate information is not provided in the transmitted frame data. This paper presents the optimal frame rate detection scheme in the sense of minimizing the frame rate detection error probability in the AWGN channel. Simulation results show that the proposed rate detection scheme can provide a gain of up to 4.4 dB over the conventional method in terms of the required bit energy to noise ratio E/sub b//N/sub 0/ at a detection error rate of 10/sup -4/ in the AWGN environment.

Future PCS (personal communication system) cellular networks will mainly be driven by high link quality, high bandwidth utilization, low power consumption and efficient network management. Power control is one of the several major techniques which could help to achieve these goals. By exploiting power control techniques, co-channel interference could be reduced and as many links as possible could be obtained with satisfactory link quality. SIR-based (signal-to-interference ratio-based) power control was proposed as a technique for managing co-channel interference in cellular radio systems. Furthermore, new distributed autonomous feedback power control methods were introduced to achieve excellent performance without the difficult centralized control used in SIR-based methods. Unfortunately, the implementation of those power control algorithms is still challenging owing to the precision of SIR. The main aim of this paper is to investigate an uplink power control algorithm which depends indirectly on the signal-to-noise ratio in the TDMA (time division multiple access) cellular system. Simulation of the prototype hardware implementation of the receiver baseband signal processing based on the PACS (personal access communications system) specification is used as the main approach to explore the performance evaluation of this power control technique. According to simulation results, suitable values of those parameters used in this power control algorithm are derived, and the minimum frequency reuse factor under different propagation environments is also obtained for PACS under power control. © 1998 John Wiley & Sons, Ltd.

Extensive empirical studies presented in this article confirm that the quality of radio communication between low-power sensor devices varies significantly with time and environment. This phenomenon indicates that the previous topology control solutions, which use static transmission power, transmission range, and link quality, might not be effective in the physical world. To address this issue, online transmission power control that adapts to external changes is necessary. This article presents ATPC, a lightweight algorithm for Adaptive Transmission Power Control in wireless sensor networks. In ATPC, each node builds a model for each of its neighbors, describing the correlation between transmission power and link quality. With this model, we employ a feedback-based transmission power control algorithm to dynamically maintain individual link quality over time. The intellectual contribution of this work lies in a novel pairwise transmission power control, which is significantly different from existing node-level or network-level power control methods. Also different from most existing simulation work, the ATPC design is guided by extensive field experiments of link quality dynamics at various locations over a long period of time. The results from the real-world experiments demonstrate that (1) with pairwise adjustment, ATPC achieves more energy savings with a finer tuning capability, and (2) with online control, ATPC is robust even with environmental changes over time.

Extensive empirical studies presented in this paper confirm that the quality of radio communication between low power sensor devices varies significantly with time and environment. This phenomenon indicates that the previous topology control solutions, which use static transmission power, transmission range, and link quality, might not be effective in the physical world. To address this issue, online transmission power control that adapts to external changes is necessary. This paper presents ATPC, a lightweight algorithm of Adaptive Transmission Power Control for wireless sensor networks. In ATPC, each node builds a model for each of its neighbors, describing the correlation between transmission power and link quality. With this model, we employ a feedback-based transmission power control algorithm to dynamically maintain individual link quality over time. The intellectual contribution of this work lies in a novel pairwise transmission power control, which is significantly different from existing node-level or network-level power control methods. Also different from most existing simulation work, the ATPC design is guided by extensive field experiments of link quality dynamics at various locations and over a long period of time. The results from the real-world experiments demonstrate that 1) with pairwise adjustment, ATPC achieves more energy savings with a finer tuning capability and 2) with online control, ATPC is robust even with environmental changes over time.

Efficient power control is of great importance in the design of high capacity cellular radio systems. Optimum power control scheme, in the sense that it minimises the outage probability, has been fully investigated for FDMA/TDMA cellular systems. The authors propose optimum power control and several centralised power control algorithms for CDMA cellular systems. Simulation results indicate that the optimum power control scheme outperforms the perfect average power control algorithm by ~1.9 dB under the IS-95 defined radio condition.

In an LEO satellite CDMA system, power control can only be used to combat long-term signal loss due to long round trip delay, which calls for different considerations on power control algorithms. Based on the criteria of fast response, small overcompensation, oscillation-avoiding, and minimum power control error, the behavior of the transient response of fixed step power control, adaptive power control, and multistep power control are investigated and compared. A new multistep power control algorithm is proposed for LEO satellite communication systems suffering from high variation in the envelope of the received signal, i.e., high dynamics in slow fading.

In vehicular ad hoc networks (VANETs), transmission power is a key factor in several performance measures, such as throughput, delay, and energy efficiency. Vehicle mobility in VANETs creates a highly dynamic topology that leads to a nontrivial task of maintaining connectivity due to rapid topology changes. Therefore, using fixed transmission power adversely affects VANET connectivity and leads to network performance degradation. New cross‐layer power control algorithms called (BL‐TPC 802.11MAC and DTPC 802.11 MAC) are designed, modeled, and evaluated in this paper. The designed algorithms can be deployed in smart cities, highway, and urban city roads. The designed algorithms improve VANET performance by adapting transmission power dynamically to improve network connectivity. The power adaptation is based on inspecting some network parameters, such as node density, network load, and media access control (MAC) queue state, and then deciding on the required power level. Obtained results indicate that the designed power control algorithm outperforms the traditional 802.11p MAC considering the number of received safety messages, network connectivity, network throughput, and the number of dropped safety messages. Consequently, improving network performance means enhancing the safety of vehicle drivers in smart cities, highway, and urban city.

The performance of a multiuser wireless network using OFDM, combined with power control and adaptive beamforming for uplink transmission is presented. An adaptive power control algorithm is exploited to achieve the desired signal to noise and interference ratio (SINR) at each subchannel and increase the power efficiency of the mobile transmitter. At the receiver side, the base station uses an antenna array to optimize the SNR-power efficiency, and attenuate the interference from other users dramatically. Therefore, we can achieve a better overall error probability with a fixed total power. A distributed iterative algorithm is used to jointly update the transmission power and the beamformer weights at each subchannel so that it can converge to the optimal solution for both power and beamforming vectors at each subchannel. The algorithm uses only the interference measured locally by the transmitter. Unlike most of the loading algorithms which optimize the bit distribution and subchannel power allocation for a single transmitter this approach tries to optimize the power allocation and decrease the interference for the whole network.

With a narrowband multiuser detector (MUD), multiple users can simultaneously share the same channel without using a bandwidth expanding signature code when sufficient power differences at the receiver are maintained. In this paper, we estimate the capacity that can be achieved in a hypothetical cellular system with centralized power control, using a narrowband MUD based on successive cancellation. The power control algorithm is adapted to multiple users per channel in a cell. Capacity results from simulations based on user removal are presented for three removal algorithms. It is shown that the narrowband MUD has a significant potential for capacity gain due to a tighter packing of users in a channel.

Most of the power control (PC) algorithms assumed that the link gains are fixed, and the power control command can take any value in the real field. These two assumptions are unrealistic in actual communication systems, since link gains are time varying and power control commands must be sent over capacity limited channels. In this paper, we propose a binary feedback power control algorithm (BFPC) for time-varying link gain environments. This algorithm can possibly be implemented as a 1-bit increase/decrease power control command, and we construct a connection between the link gains and the step-size of the proposed algorithm. It is shown that the proposed algorithm drives the CIR to an interval in time-varying link gain environments. Simulation results show that the proposed algorithm is more robust against link gains changes as compared to Foschini and Miljanic's distributed algorithm (FMA) and proportional power control algorithm (PropPC), and the proposed algorithm can be adopted in practical mobile communication systems.

In wireless communication systems, mobile users adapt to a time varying radio channel by regulating transmitter powers. This power control is intended to provide each user an acceptable connection, as measured by a carrier to interference ratio (CIR), by eliminating unnecessary interference. It is important that a power control algorithm can converge quickly to a fixed point at which either all users have acceptable connections or an infeasibility can be detected. In this work, we show that an iterative power control and base station assignment algorithm based on CIR measurements converges to a unique fixed point at a geometric rate. This conclusion is shown to hold even if some or all of the users are subject to maximum power constraints. The rate of convergence is evaluated by simulation of a one dimensional CDMA system.

Power control for forward link soft handoff users in cellular CDMA systems is important in order to obtain good forward link performance. The two existing schemes in the 3GPP specification, balancing power control (BPC) and site selection diversity transmission (SSDT), both have shortcomings due to their static properties. In this paper, we propose a dynamic power control scheme which can modify the power control policy according to changing environment situations. We apply a distributed reinforcement learning (DRL)-based coordinated decision-making method to achieve dynamic power control. The main idea is to learn the optimal transmission power levels from BSs under different environmental situations with multiple mobile users. Our simulation results show that the proposed scheme effectively combines the advantages of existing schemes in order to maximize the forward link capacity.