Allocation Of Power Levels Research Articles

Digital Twin Empowered Heterogeneous Network Selection in Vehicular Networks With Knowledge Transfer

Digital twin (DT) has emerged as a promising technology to create digital replicas of physical vehicles to facilitate driving in Internet of Vehicles (IoV). However, due to the uneven distribution of vehicles in the networks and the dynamics of heterogeneous wireless links, how to optimize the connection along the vehicle's trip between the vehicle and its DT to achieve the lowest cost ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.</i> , delay and energy consumption) is a fundamental challenge. In this paper, we investigate the joint network selection and power level allocation problem in the data synchronization issue between vehicles and DTs in the heterogeneous access networks. In order to better use the information shared by DT to facilitate the data synchronization process, we propose a learning-based heterogeneous network selection scheme in DT empowered IoV. First, we consider the data divided into blocks and model the data synchronization problem as a Markov Decision Process (MDP) to minimize the long-term cost in terms of the delay and energy consumption. Based on the information obtained from the digital twin communications, we develop an actor-critic learning approach to solve the MDP problem with the block-level state method, and obtain the optimal network selection strategy for the vehicles. In addition, we explore the capability of digital twins by applying transfer learning. The vehicles are divided into two types, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.</i> , learner vehicles and expert vehicles, so that the knowledge can be transferred from the expert vehicles to the learner vehicles to effectively improve the learning efficiency and decrease the data synchronization latency. Extensive experiments demonstrate that our scheme can effectively find the optimal network selection policy and achieve the fast convergence and better performance compared with existing related approaches.

User-specific power level allocation optimization for OFDM-NOMA in a multi-user RoF system.

In this Letter, we propose a digital signal processing (DSP) -aided technique to optimize the power ratio among users for orthogonal frequency division multiplexing (OFDM) -based non-orthogonal multiple access (NOMA) in an integrated optical fiber and millimeter wave (mmWave) wireless communication system. In this way, a central or distributed unit can leverage the proposed techniques to maintain the uniformity of the signal-to-noise ratios (SNRs) among subcarriers without requiring any channel information feedback. The proposed mechanism can facilitate the power allocation management by treating all subcarriers equally as an independent channel. As an illustration, multiple NOMA scenarios, in which a near user with 10 km fiber transmission and far user with either longer fiber distance or additional wireless propagation, are experimentally investigated. Experimental results demonstrate that when the conventional OFDM-NOMA without the proposed DSP-aided technique is used, the optimal power ratios vary rapidly when the subcarrier quality index changes due to high-frequency fading in a mmWave radio over fiber (RoF) system, whereas, by using the proposed techniques, including both orthogonal circulant matrix transform and discrete Fourier transform, the optimal power ratios on all effective subcarriers are optimized at the same level and the users' performance is significantly improved.

A Deep Reinforcement Learning Based D2D Relay Selection and Power Level Allocation in mmWave Vehicular Networks

5G millimeter wave (mmWave) communication is an efficient technique for low delay and high data rate transmission in vehicular networks. Due to the high path loss in 5G mmWave band, 5G base stations need to be densely deployed, which may result in great deployment expenditures. In this letter, we jointly consider a relay selection problem in multihop 5G mmWave device to device (D2D) transmissions and a power level allocation problem of mmWave D2D links. We propose a centralized hierarchical deep reinforcement learning based method to find an optimal solution for the problem. The proposed method does not rely on the information of links, and it tries to find an optimal solution based on the information of vehicles. Simulation results show that the convergence of the proposed method, and the transmission delay performance of proposed method is better than a link-quality-prediction based method, and close to a link-quality-known method.

Mitigation of nonlinearities in fiber optic DWDM system

To meet the growing internet data traffic, transmission capacity of fibers has to be increased. For that Dense Wavelength Division Multiplexing (DWDM) technique has been used nowadays. However, there is a nonlinear distortion which degrades the transmitted signal and hence decreases the overall system performance. The nonlinearities that arise in WDM systems are Cross Phase Modulation (XPM), Stimulated Raman Scattering (SRS) and Four Wave Mixing (FWM). Also it is found that these nonlinearities depend upon input power, dispersion and channel spacing. In this paper two methods have been proposed to eliminate FWM and SRS effect. Firstly, the fiber optic link has been analyzed by increasing the input power. From the analysis it is found that the FWM effect get increased by increasing the input power. But the transmission power should be optimum to transmit the information in long haul fiber optic link. The FWM effect is reduced by placing the Circular Polarizers alternatively in each transmitter before passing through the fiber link. Another method which has been proposed to eliminate SRS is optimum allocation of input power. The unwanted power tilt due to SRS effect is reduced by allocating the transmitted power randomly. The simulation studies are carried out using OPTSIM and OPTISYSTEM software. The simulations have been carried out for multichannel systems with equal spacing. It is found that the optimum power level allocation also improved the system performance.

Distributed Power and Channel Allocation for Cognitive Femtocell Network Using a Coalitional Game in Partition-Form Approach

The cognitive femtocell network (CFN) integrated with cognitive-radio-enabled technology has emerged as one of the promising solutions to improve wireless broadband coverage in indoor environments for next-generation mobile networks. In this paper, we study a distributed resource allocation that consists of subchannel- and power-level allocation in the uplink of the two-tier CFN comprised of a conventional macrocell and multiple femtocells using underlay spectrum access. The distributed resource allocation problem is addressed via an optimization problem, in which we maximize the uplink sum rate under constraints of intratier and intertier interference while maintaining the average delay requirement for cognitive femtocell users. Specifically, the aggregated interference from cognitive femtocell users to the macrocell base station (MBS) is also kept under an acceptable level. We show that this optimization problem is NP-hard and propose an autonomous framework, in which the cognitive femtocell users self-organize into disjoint groups (DJGs). Then, instead of maximizing the sum rate in all cognitive femtocells, we only maximize the sum rate of each DJG. After that, we formulate the optimization problem as a coalitional game in partition form, which obtains suboptimal solutions. Moreover, distributed algorithms are also proposed for allocating resources to the CFN. Finally, the proposed framework is tested based on the simulation results and shown to perform efficient resource allocation.

Joint iterative power allocation and linear interference suppression algorithms for cooperative DS-CDMA networks

This work presents joint iterative power allocation and interference suppression algorithms for spread spectrum networks, which employ multiple hops and the amplify-and-forward cooperation strategy for both the uplink and the downlink. The authors propose a joint constrained optimisation framework that considers the allocation of power levels across the relays subject to individual and global power constraints and the design of linear receivers for interference suppression. The authors derive constrained linear minimum mean-squared error (MMSE) expressions for the parameter vectors that determine the optimal power levels across the relays and the linear receivers. In order to solve the proposed optimisation problems, the authors develop cost-effective algorithms for adaptive joint power allocation, and estimation of the parameters of the receiver and the channels. An analysis of the optimisation problem is carried out and shows that the problem can have its convexity enforced by an appropriate choice of the power constraint parameter, which allows the algorithms to avoid problems with local minima. A study of the complexity and the requirements for feedback channels of the proposed algorithms is also included for completeness. Simulation results show that the proposed algorithms obtain significant gains in performance and capacity over existing non-cooperative and cooperative schemes.

Joint Power Allocation and Interference Mitigation Techniques for Cooperative Spread Spectrum Systems with Multiple Relays

This paper presents joint power allocation and interference mitigation techniques for the downlink of spread spectrum systems which employ multiple relays and the amplify and forward cooperation strategy. We propose a joint constrained optimization framework that considers the allocation of power levels across the relays subject to an individual power constraint and the design of linear receivers for interference suppression. We derive constrained minimum mean-squared error (MMSE) expressions for the parameter vectors that determine the optimal power levels across the relays and the linear receivers. In order to solve the proposed optimization problem efficiently, we develop joint adaptive power allocation and interference suppression algorithms that can be implemented in a distributed fashion. The proposed stochastic gradient (SG) and recursive least squares (RLS) algorithms mitigate the interference by adjusting the power levels across the relays and estimating the parameters of the linear receiver. SG and RLS channel estimation algorithms are also derived to determine the coefficients of the channels across the base station, the relays and the destination terminal. The results of simulations show that the proposed techniques obtain significant gains in performance and capacity over non-cooperative systems and cooperative schemes with equal power allocation.

Study of Certain Subband-based Adaptive Modulation Schemes in an OFDM System

In applying adaptive schemes to an OFDM system to adaptively adjust the trans- mission format based on channel state information, a practical scheme would group the subcarriers into similar-quality subbands to reduce the associated modem mode-signaling requirements. One way to determine the modulation mode for a speciflc subband is based on the average signal- to-noise ratio (SNR) of the subband. To flnd the optimal switching levels, knowledge of the probability density function of this average SNR is required. Another popular way to determine the modulation mode is based on the SNR of the worst subcarrier of the suband, which may rep- resent an overconservative choice of order statistic. This approach can be extended to deploying other statistic as well, for example, the second or the third worst statistic. Analysis of the above approaches is the focus of this study, and performances of these schemes are compared through numerical simulations. DOI: 10.2529/PIERS061113041022 For an OFDM system in wireless communication, due to multipath fading, subcarriers experi- ence signal-to-noise ratio (SNR) degradation to varying degree. Adaptive modulation schemes are efiective to mitigate such detrimental efiect, where in principle the transmitted power and bit rate of each subcarrier are allowed to change dynamically according to channel variations. Yet such a full treatment implies high complexity in modem hardware and high signalling overhead over the feedback channel from the receiver to the transmitter, a scheme that may not be plausible in high-speed wireless data applications. Such concern leads to some suboptimal schemes. Grunheid etal. (1) and Keller and Hanzo (2) proposed to group the subcarriers into similar-quality subbands with single constellation being used for the subcarriers within a subband. Dardari (4) proposed an ordered subcarrier selection algorithm where among the available N subcarriers only the K sub- carriers (KN) with the highest SNRs are used, to which uniform bit and power level allocation are applied. For a mode-switching-assisted adaptive modulation scheme, the bit-error-rate (BER) and through- put performances are determined by the set of switching levels. Chung and Goldsmith (4) and Choi and Hanzo (5) analyzed for single carrier system the constant power variate rate adaptive mod- ulation scheme. The optimal switching levels that maximize the average bits-per-symbol (BPS) throuput for a target average BER are found to depend on the channel quality statistics. In ex- tending this technique to multicarrier system where subband based adaptive modulation scheme is adopted, Keller and Hanzo (2) proposed to use the subcarrier experiencing the worst SNR. This approach may appear somehow conservative, which motivates us to analyze the problem using other order statistic of the subcarrier SNRs, such as the second or the third order worst statistic. Another plausible approach is to use the average SNR of all the subcarriers within a subband, where the optimal switching levels can be determined by using the probability density function (pdf) of the average SNR in conjunction with Lagrangian optimization technique. These approaches form the body of the current study. In the order statistic approach, the subcarriers are usually assumed to be independently and identically distributed (i.i.d) Rayleigh fading channels for mathematical convenience (3), although they are in general correlated. Consider a subband containing P subcarriers, where the pdf of the SNR ∞ of each subcarrier is f∞ (∞) = 1 ∞ e

A novel capacity analyzing method for multimedia CDMA systems based on power level allocation

A novel method is proposed to analyze the capacity of future Code Division Multiple Access (CDMA) systems carrying multimedia services. The power level allocation is firstly investigated to meet each call’s Bit Error Rate (BER) requirement, then the system capacity is defined from the conditions for the existence of the physical meaning of these power levels. Simulation results have shown that the capacity analyzing methods can be well used in the performance evaluation of the system accommodating heterogeneous services and the spectral efficiency of this scheme is higher than the existing ones.

Optimal resource allocation for wireless video over CDMA networks

We present a multiple-channel video transmission scheme in wireless CDMA networks over multipath fading channels. We map an embedded video bitstream, which is encoded into multiple independently decodable layers by 3D-ESCOT video coding technique, to multiple CDMA channels. One video source layer is transmitted over one CDMA channel. Each video source layer is protected by a product channel code structure. A product channel code is obtained by the combination of a row code based on rate compatible punctured convolutional code (RCPC) with cyclic redundancy check (CRC) error detection and a source-channel column code, i.e., systematic rate-compatible Reed-Solomon (RS) style erasure code. For a given budget on the available bandwidth and total transmit power, the transmitter determines the optimal power allocations and the optimal transmission rates among multiple CDMA channels, as well as the optimal product channel code rate allocation, i.e., the optimal unequal Reed-Solomon code source/parity rate allocations and the optimal RCPC rate protection for each channel. In formulating such an optimization problem, we make use of results on the large-system CDMA performance for various multiuser receivers in multipath fading channels. The channel is modeled as the concatenation of wireless BER channel and a wireline packet erasure channel with a fixed packet loss probability. By solving the optimization problem, we obtain the optimal power level allocation and the optimal transmission rate allocation over multiple CDMA channels. For each CDMA channel, we also employ a fast joint source-channel coding algorithm to obtain the optimal product channel code structure. Simulation results show that the proposed framework allows the video quality to degrade gracefully as the fading worsens or the bandwidth decreases, and it offers improved video quality at the receiver.

Ordered Subcarrier Selection Algorithm for OFDM-Based High-Speed WLANs

In this letter, a low-complexity and low-overhead adaptive bit-loading algorithm for wireless multicarrier schemes is proposed and analyzed. It is based on the diversity gain obtained through the ordering and selection of the more reliable subcarriers. Higher order modulations are used to compensate for the reduced subcarrier utilization. On the contrary to other bit-loading algorithms, it does not require nonuniform bit and power level allocation among subcarriers, thus drastically reducing the modem hardware complexity and making it attractive as a possible extension of existing high-speed wireless local-area network standards. System performance is analyzed in different configurations and conditions, including a realistic 5-GHz propagation scenario. Comparison with optimal adapted and unadapted solutions is also made. Finally, the effect of unideal feedback of the channel state information is analyzed showing the robustness and the low overhead required of the new scheme.