Mohammed Elmusrati

Multi-objective distributed power control algorithm

In this paper a new distributed power control algorithm is proposed. It is based on the minimization of multiple objectives. The objectives are to keep the transmitted power as close to the minimum power as possible and simultaneously, to hold the carrier to interference ratio (CIR) close to the given target. The multi-objective optimization problem is transformed into a single-objective optimization problem. Its solution results in a new, efficient power algorithm, which is simple to implement. Simulations demonstrate that it converges faster than the conventional power control algorithms. Also, the average transmitted power is less than the average transmitted power using the conventional methods with comparable quality of service (QoS). Noisy, dynamical environment is assumed in the simulations. The algorithm has been modified to work with quantized carrier to interference ratio (CIR). A new soft dropping algorithm based on a multi-objective technique has been developed.

Multi-objective distributed power and rate control for wireless communications

In this paper, we introduce a new fully distributed algorithm for combining power and rate control in wireless communication systems. The algorithm is based on minimizing a multi-objective definition of an error function. In this paper, we defined three objectives. The objectives are: 1) minimizing the transmitted power, (2) achieving at least the target carrier to interference ratio (CIR) which id defined at the minimum data rate, and 3) achieving the maximum CIR which is defined at maximum data rate. An optimized solution can be obtained by using a multi-objective optimization technique. The suggested algorithm is simple to implement and very efficient. The simulations carried out on the UMTS specifications indicate that our algorithm give a very good performance in terms of data rate, outage probability, convergence speed and transmission power consumption.

Performance analysis of random uniform power allocation for wireless networks in Rayleigh fading channels

When there is no feedback channels in wireless sensor networks or when the sensors are deaf (cannot listen to the feedback channels), the conventional and practical method for power allocation is to use fixed power transmission. This method has many limitations such as near–far problems where the relatively far away sensors are blocked by near sensors and also the unnecessarily high power consumption for good channel sensors. One recent proposal to overcome such limitations is to use uniform random power allocation for terminals. In that work the system performance is analysed for static channels (i.e. snapshot assumption), where it shows that there is a considerable obtained gain when using uniform random power allocation over fixed power. An important question is about the performance of such transmission power strategy in case of a more realistic channel scenario such as Rayleigh fading channels. This paper answers this question. Detailed mathematical analysis as well as Monte-Carlo simulations for the system performance in Rayleigh fading channels are given in this paper. We show that the performance of uniform power allocation is much worse in case of fading channels than in static channels. Almost there is no gain of using uniform random power over fixed power in terms of average probability of outage. However, uniform random power may considerably reduce the total power consumption at small degradation of the average performance. This can be critical feature in energy constrained networks. Copyright

Random Switched Beamforming for Uplink Wireless Sensor Networks

Integration of beamforming to sensors is very beneficial for a reduction of transmission power consumption and for improvement of the overall system performance. Unfortunately, the beamforming brings up usually two serious problems. Firstly, the beamforming adaptation needs a lot of processing and hence the power consumption is increased, which is not desirable in the energy constrained devices such as wireless sensors. Secondly, there is not always a feedback channel available to inform the transmitter about the channel to adapt the antennas weights. This paper proposes a random beam-switching which relaxes the above two problems and yet achieves important benefits such as fairness and performance. A detailed mathematical analysis of the proposed algorithm is given. The simulations show the improved performance of the suggested beam-switching algorithm compared to the conventional omni-directional antennas.

Random Power Control for Uncorrelated Rayleigh Fading Channels

When the channel measurement update rate is very slow compared to the channel fluctuations, the performance of conventional power control algorithms is greatly reduced. In this paper we introduce novel method to update the transmit power in such extreme situations. We propose to use random power allocation with certain distribution function and then using the channel measurements to update the statistics of this random power rather the power value itself. The truncated inverted exponential distribution is one candidate for the power distribution which is used in this paper. This distribution has one parameter which can be easily updated according to the channel quality. The signal-to-interference and noise ratio (SINR) is used as an indicator for the channel quality. The probability of outage when using the proposed power allocation is also given in mathematical form. Simulations show that, one may improve the average SINR when using the proposed algorithm compared to the conventional distributed power control algorithm.

Multi-objective totally distributed power and rate control for wireless communications

In this paper, we introduce a new totally distributed algorithm for combining power and rate control in wireless communication systems. The main feature of this algorithm over the multi-objective distributed power and rate control (MODPRC) algorithm presented in M. Elmusrati and H. Koivo (2003), is that the actual CIR is not needed to update the power and the rate. It works with the on-off commands of the power control in existing cellular communication systems. The algorithm is based on minimizing a multi-objective cost function. In this paper we defined three objectives. The objectives are minimizing the transmitted power, achieving at least the minimum carrier to interference ratio (CIR), which is defined at the minimum data rate, and achieving the maximum CIR, which is defined at maximum data rate. An optimized solution can be obtained by using a multi-objective optimization technique. The suggested algorithm is simple to implement and efficient. The simulations carried out on the UMTS specifications indicate that our algorithm gives a very good performance in terms of data rate, outage probability, and transmission power consumption.

Fully distributed power control algorithm with one bit signaling and nonlinear error estimation [mobile radio systems]

In this paper, we suggest a method to estimate the carrier to interference ratio (CIR) information of the uplink using the power control ON-OFF commands at the mobile station (MS). The estimated CIR information is used to adjust the transmitted power from the mobile terminal using the distributed constrained power control (DCPC) algorithm. The main advantage of our algorithm is that it can improve the performance of power control without any increase in power control signaling. The suggested algorithm is compared with the conventional fixed step power control (FSPC) algorithm by computer simulations. Considerable improvements in system performance are observed when using the suggested algorithm in comparison with the FSPC algorithm.

Centralized algorithm for the tradeoff between total throughput maximization and total power minimization in cellular systems

In this paper we have constructed a centralized power control algorithm based on the tradeoff between the maximization of the total throughput of the users and the minimization of their total transmitted power in cellular systems. Power control algorithm for total throughput maximization has been proposed in K. Chawla et al. (1998). In our algorithm, we use the same throughput maximization objective, but another objective for power minimization has been added. The multi-objective optimization problem has been solved using weighting method. A centralized power control algorithm has been obtained. The algorithm is a scaled version of the maximum throughput algorithm obtained in K. Chawla et al. (1998). The simulations show that at low additive white noise levels the total transmitted power can be reduced up to 95% compared with the algorithm given in K. Chawla et al. (1998) while the total throughput has reduced only by less than 3%.

Kalman filters applications in radio resource scheduling of wireless communication

We investigate the applications of Kalman filters as radio resource scheduler. A novel algorithm is proposed. It is well known fact that the Kalman filter is the optimum linear tracking device on the basis of second order statistics. This feature motivates us to apply the Kalman filter in this type of applications. The proposed Kalman radio resource scheduler is a distributed algorithm. The convergence properties of the proposed algorithm are studied. The simulations show that the proposed algorithm is able to track the fast variations of channel gain and achieves the required quality of service. It has fast convergence speed in terms of transmitted power and outage.

Performance Analysis of Wireless Deaf CDMA Sensor Networks in Fading Channels

In this letter we study the performance of wireless sensor networks in Rayleigh fading channel, transmitted power of every sensor is assumed to be fixed during the packet transmission. The probability of packet loss (or instantaneous outage) and the accessibility are used as the performance measures. The accessibility is defined in this letter as the probability that the sensor having the weakest link gets successful access. Closed form mathematical representation of the performance is given without Gaussian approximation of the interference. Monte Carlo simulations are provided to validate the results.