Dynamic Power Allocation Scheme Research Articles

CDMA-Based Dynamic Power and Bandwidth Allocation (DPBA) Scheme for Multiclass EPON: A Weighted Fair Queuing Approach

Multiclass systems with different quality of service (QoS) requirements are essential in today's Ethernet passive optical networks (EPONs). In this paper, we propose a code division multiple-access-enabled dynamic power and bandwidth allocation (DPBA) algorithm for a multiclass system. The novelty of the proposed algorithm is the resource allocation components: power control and bandwidth allocation. Both resources are related and optimized through the weights of the weighted round-robin scheduler in a way to meet the physical layer signal to interference ratio and the network layer packet delay requirements for every class of users. Our objective is to offer a differentiated class of services for all optical network units while optimizing network performance and guaranteeing fairness between different classes. A closed-form solution for the optimal power and bandwidth allocation using the DPBA algorithm is analytically derived. It is shown that the proposed algorithm can radically enhance the network performance in terms of packet delay, throughput, queue size management, transmission cycle time, and class of service fairness while guaranteeing the QoS requirements for all classes.

A General Power Allocation Scheme to Guarantee Quality of Service in Downlink and Uplink NOMA Systems

In this paper, a novel dynamic power allocation scheme is proposed to downlink and uplink non-orthogonal multiple access (NOMA) scenarios with two users for more flexibly meeting various quality of service requirements. The exact expressions for the outage probability and the average rate achieved by the proposed scheme, as well as their high signal-to-noise ratio approximations, are established. Compared with the existing works, such as NOMA with fixed power allocation and cognitive radio inspired NOMA, the proposed scheme can: 1) strictly guarantee a performance gain over conventional orthogonal multiple access; and 2) offer more flexibility to realize different tradeoffs between the user fairness and system throughput. Monte Carlo simulation results are provided to demonstrate the accuracy of the developed analytical results and the performance gain of the proposed power allocation scheme.

Outage Performance for Dynamic Power Allocation in Hybrid Non-Orthogonal Multiple Access Systems

In this letter, we propose a novel dynamic power allocation scheme for hybrid non-orthogonal multiple access (DH-NOMA). The exact expressions for the outage probabilities and their asymptotic approximations at high signal-to-noise ratio are derived in DH-NOMA systems. Both Monte Carlo simulations and analytical results are used to compare the proposed scheme with the existing works, such as NOMA based on fixed power allocation (F-NOMA) and cognitive radio inspired NOMA (CR-NOMA). The provided results demonstrate that the DH-NOMA scheme can always achieve better outage performance than the traditional orthogonal multiple access, and achieve a more balanced tradeoff between the two user individual rates than F-NOMA and CR-NOMA.

Energy‐efficient dynamic power allocation in multi‐antenna transmissions with imperfect channel estimation and feedback

A dynamic power allocation scheme is proposed to maximise the energy efficiency (EE) for multi-antenna transmissions when both the imperfect channel estimation and feedback are considered. The lower bounded ergodic EE is given by the temporal correlation analysis from the Kalman estimation and the differential codebook-based feedback of the Gauss–Markov channel, based on which both the powers of data and training are adaptively optimised. Simulations show that the proposed dynamic power allocation scheme outperforms the traditional power allocation schemes.

Coverage Self-Optimization for Randomly Deployed Femtocell Networks

There is an ever increasing demand on wireless communication systems for improved indoor coverage, greater capacity and enhanced user services. Energy efficient, small scale femtocell networks deployed in home, office and other indoor environments are one of the promising means of satisfying these demands. They can provide substantial benefits to both operators and users, such as a reduction in capital expenditures and operational expenditures, easy plug-and-play and optimized indoor coverage. Because of the random deployment behavior by the users, femtocell base stations (FBSs) should have cognitive position awareness, automatic parameter tuning and learning abilities. This will allow for self-optimization of the indoor coverage with the minimal interference to outdoor users. This paper first proves that the optimal coverage radii for FBS exist in typical indoor environments with position awareness enabled technology. Then, a dynamic power allocation technique for FBS is designed and analyzed in this paper by considering the path loss and different wall penetration conditions. To further enable the intelligent coverage self-optimization for randomly deployed indoor FBSs, a novel joint dynamic power allocation and antenna pattern selection scheme using the artificial neural network is proposed. Performance results are presented to illustrate the effectiveness and accuracy of the proposed coverage technique for randomly deployed femtocell networks.

Optimal Resource Allocation in Heterogeneous MIMO Cognitive Radio Networks

The optimal resource allocation in MIMO cognitive radio networks with heterogeneous secondary users, centralized and distributed users, is investigated in this work. The core aim of this work is to study the joint problems of transmission time and power allocation in a MIMO cognitive radio scenario. The optimization objective is to maximize the total capacity of the secondary users (SUs) with the constraint of fairness. At first, the joint problems of transmission time and power allocation for centralized SUs in uplink is optimized. Afterwards, for the heterogeneous case with both the centralized and distributed secondary users, the resource allocation problem is formulated and an iterative power water-filling scheme is proposed to achieve the optimal resource allocation for both kinds of SUs. A dynamic optimal joint transmission time and power allocation scheme for heterogeneous cognitive radio networks is proposed. The simulation results illustrate the performance of the proposed scheme and its superiority over other power control schemes.

Optimal user scheduling and power control in multi-user cognitive broadcast systems

Cognitive radio systems should not only have the ability to sense and exploit “frequency spectrum holes”, but also the ability to sense and utilize “spatial spectrum holes”. In this paper, we consider the issue of maximizing the throughput of the cognitive systems by fully utilizing “spatial spectrum holes” brought in by multiple cognitive users, in the scenario where a pair of licensed users and a cognitive broadcast system share multiple spectrum bands. By exploiting the channel reciprocity under the premise that the licensed system adopts the time-division-duplexing (TDD) mode, we propose a more practical cognitive access scheme that can sense the interference at the licensed user caused by the cognitive transmitter, based on the existing feedback signals from the licensed user to the licensed base station. Taking both interferences from the licensed base station to the cognitive receiver and from the cognitive transmitter to the licensed user into consideration, we investigate the optimal user scheduling and power allocation scheme that can maximize the ergodic sum rate of the cognitive system. We show that scheduling the user whose channel gain to interference and noise ratio (CGINR) is the largest for each frequency band is optimal. We also derive the dynamic power allocation scheme meeting the three practical constraints, i.e., the transmitter’s average transmission power constraint, the power amplifier’s instantaneous transmission power constraint, and the interference power constraint at the licensed user. The result shows that in different coherent time intervals and different frequency bands, the power allocation has a multi-level waterfilling structure. Theoretical analysis shows that the strategy scheduling user with the largest CGINR introduces significant performance improvement compared with the traditional strategy scheduling user with the largest channel gain to noise ratio (CGNR). We also illustrate the impact of power constraints and the number of users on system performance by simulation.

Novel scheme for interference avoidance in cognitive radio based cellular networks

The cognitive radio (CR) technology is believed to improve the spectrum efficiency. However, the interference problem has become a critical issue due to the coexistence of primary systems and CR systems. In this paper, the interferences in CR based cellular networks are discussed. Interference scenarios are analyzed, considering different interference sources. Meanwhile, an improved model named ‘Cognitive Interference Ring’ is introduced to describe the interference range of each secondary user (SU). Depending on the above analysis, graph coloring based dynamic power allocation (GCDPA) scheme is proposed for interference avoidance. Simulation results demonstrate that in CR based cellular networks, the interferences to primary users (PUs) can be effectively mitigated with the proposed GCDPA scheme, and the system throughput and power efficiency are both improved.

Chunk-Based Resource Allocation in OFDMA Systems—Part II: Joint Chunk, Power and Bit Allocation

By grouping a number of adjacent subcarriers into a chunk, resource allocation can be carried out chunk by chunk in orthogonal frequency division multiple access (OFDMA) systems. Chunk-based resource allocation is an effective approach to reduce the complexity of resource allocation in OFDMA systems. In this paper, a chunk-based resource allocation scheme, i.e. joint chunk, power and bit allocation, is proposed and analyzed by maximizing the throughput under a total transmit power constraint. A scaling factor is introduced to achieve optimal allocation. Considering the digital nature of bits per symbol per subcarrier (bits/symbol/subcarrier), a digitization process is proposed to digitize the theoretically allocated bits/symbol/subcarrier to integer. System parameters, such as the power constraint, number of users, coherence bandwidth, number of subcarriers and number of chunks, are introduced and their impacts on the average throughput are studied. The performance of the dynamic power allocation scheme is compared with the fixed power allocation scheme. The numerical results show that the theoretical throughput of the fixed power allocation scheme is quite close to that of the dynamic power allocation scheme. However, when the digital nature of bits/symbol/subcarrier is considered, the average throughput of the dynamic power allocation outperforms the fixed power allocation scheme.

Power Control for Uplink Transmission With Mobile Users

In this paper, we introduce an uplink transmission model with mobile users, where each user maximizes his/her utility to achieve the best performance. We propose a power allocation scheme for each mobile user when all channel information is available. Moreover, we illustrate that one user would expect to predict the aggregate interference to maximize the utility when the channel information is incomplete. It is shown that this approach forms a game with incomplete information. We demonstrate the prediction rules that can help the mobile users dynamically adjust predictions and apply the Kalman filter to tackle measurement noises. We also illustrate the theoretical bound for the difference between the utility with prediction and that with complete information. Moreover, applying dynamic programming from control theory, we give a dynamic power allocation scheme based on the predictions. Simulation results indicate that our power allocation scheme with complete information and dynamic power allocation with predictions give better performance compared with the scheme with even power allocation. In addition, results under our dynamic power allocation scheme are close to those under the power allocation with complete information.

Polarization Beamforming PON Doubling Bidirectional Throughput

A low-complexity polarization multiplexed Passive Optical Network (PON) architecture based on Multiple Input Multiple Output (MIMO) polarization beamforming is experimentally demonstrated, achieving twice the throughput for both downstream and upstream transmissions. In addition, a novel dynamic power allocation scheme further improves the loss budget by up to ~1.8 dB in the downstream direction.

On the interference management in wireless multi-user networks

A study on interference management schemes in wireless multi-user networks is presented. We analyze the interference management problem in cellular networks and show that interference management is an optimization problem, for which we propose a general formulation. Using this general formulations we show that different interference management approaches are either exact or approximated solutions to this optimization problem. For each radio resource management technique, we provide a general overview and discuss its relation vis-a-vie other interference management techniques. As a case study, we then apply the proposed general formulation on the interference management in OFDM wireless networks and show that it results in a joint transmit scheduling and dynamic sub-carrier and power allocation scheme. A polynomial-time heuristic algorithm is also proposed to solve the formulated optimization problem. The distinguishing feature of the proposed scheme is that it gives in one shot, the transmission scheduling, the sub-carriers assigned to each user, and the power allocated to each sub-carrier, based on a fair and efficient framework while satisfying the delay requirements of real-time users.

An Improved Scheme on a Linear Pre-Coding Method of Multi-User MIMO Downlink Systems

An improved signal-to-jamming and noise ratio (SJNR) method is proposed for the linear precoding of multiuser MIMO downlink systems. To well balance suppression of co-channel interference and suppression of noise, the proposed method modifies the noise variance term to argument of a piecewise linear function, and then enhances the suppression of noise. A dynamic power allocation scheme is also introduced to further decrease the overall average bit error rate of the system. Simulation results prove the effectiveness of the proposed scheme.

Dynamic rate and power adaptation for forward link transmission using high-order modulation and multicode formats in cellular WCDMA networks

This paper addresses the problem of dynamic rate and power adaptation for forward link data transmission using high-order modulation and multicode formats in cellular wideband code division multiple access (WCDMA) networks. A novel framework for dynamic joint adaptation of modulation order, number of code channels (hence transmission rate), and transmission power is proposed for downlink data transmission in a cellular WCDMA system where different users have similar frame error rate (FER) requirements. Based on a general downlink signal-to-interference ratio (SIR) model, the problem of optimal dynamic rate and power adaptation is formulated, for which the rate and power allocation can be found by an exhaustive search. Two heuristic-based dynamic rate and power allocation schemes are proposed. Performance of dynamic joint rate and power adaptation under the proposed framework is evaluated for a random micromobility model using computer simulations. Also, an analytical approach to evaluate the throughput performance of dynamic rate and power adaptation using high-order modulation and multicode formats is presented.

Asymptotically optimal water-filling in vector multiple-access channels

Dynamic resource allocation is an important means to increase the sum capacity of fading multiple-access channels (MACs). In this paper, we consider vector multi-access channels (channels where each user has multiple degrees of freedom) and study the effect of power allocation as a function of the channel state on the sum capacity (or spectral efficiency) defined as the maximum sum of rates of users per unit degree of freedom at which the users can jointly transmit reliably, in an information-theoretic sense, assuming random directions of received signal. Direct-sequence code-division multiple-access (DS-CDMA) channels and MACs with multiple antennas at the receiver are two systems that fall under the model. Our main result is the identification of a simple dynamic power-allocation scheme that is optimal in a large system, i.e., with a large number of users and a correspondingly large number of degrees of freedom. A key feature of this policy is that, for any user, it depends on the instantaneous amplitude of channel state of that user alone and the structure of the policy is "water-filling." In the contest of DS-CDMA and in the special case of no fading, the asymptotically optimal power policy of water-filling simplifies to constant power allocation over all realizations of signature sequences; this result verifies the conjecture made in Verdu and Shamai (1999). We study the behavior of the asymptotically optimal water-filling policy in various regimes of number of users per unit degree of freedom and signal-to-noise ratio (SNR). We also generalize this result to multiple classes, i.e., the situation when users in different classes have different average power constraints.