Time-varying Fading Channels Research Articles

Opportunistic scheduling for a two‐way relay network using Markov decision process

In this study, the authors study transmission scheduling for a two-way relay network in time-varying fading channels, where the relay node can opportunistically use traditional one-way relay technique or network coding to forward traffic to the end nodes. They formulate a stochastic dynamic programme with the objective of minimising the long-run cost, defined as a function of both the transmission power and data transmission delay. An unconstrained Markov decision process model is developed and solved for the average and discounted cost problems. The optimal solution requires high computational and modelling complexity when the state space is large. For this reason, they develop heuristic solutions with lower complexity. For the discounted cost problem, a simulation-based dynamic programming algorithm is proposed that not only simplifies the modelling process and reduces the computational complexity, but also achieves close-to-optimum cost. For the average cost problem, a heuristic scheduling scheme is proposed, which makes transmission decisions based on estimated costs in the current and next time slots. The heuristic scheme achieves close-to-optimum cost performance while greatly reducing the computational complexity.

Relay Pre-Selection for Reducing CSI Transmission in Wireless Sensor Networks

Relay selection requires collection and transmission of channel state information (CSI) to a central node. When all relay nodes contribute in CSI transmission, the amount of power required for signaling the CSIs linearly increases with the number of relays. A central node should determine the proper number of pre-selected relays by aid of channel statistics and a decision criterion. We derive an upper bound on this number when end-to-end bit error rate is considered as the decision criterion and the source-relay channels are time-varying fading channels.

Energy Allocation and Cooperation for Energy-Efficient Wireless Two-Tier Networks

In this paper, we consider the resource allocation in two-tier wireless systems in which small-cell base stations harvest energy from renewable sources in addition to the conventional power grid. Moreover, we assume that each cell has access to an energy storage system with a limited battery capacity. We introduce new mechanisms that enable an efficient allocation of the available energy over time across the network. In doing so, we take into account the time-varying fading channel, the inter-cell interference and the fluctuations of harvested energy. In particular, we propose convergent offline algorithms to maximize the network energy efficiency while satisfying an average sum-rate constraint at each cell. Furthermore, we extend the resource allocation scheme by enabling an energy cooperation between the cells. By cooperating, they can exchange their harvested energy through a smart-grid power infrastructure. Using numerical simulations, we verify the convergence of the proposed algorithms and analyze the efficacy of the resource allocation and energy cooperation schemes.

An Efficient Practical MIMO–OFDM Scheme with Coded Modulation Diversity for Future Wireless Communications

An efficient coded modulation diversity scheme is proposed to improve the performance of multiple-input-multiple-output orthogonal-frequency-division-multiplexing (MIMO---OFDM) systems in frequency-selective time-varying fading channels. By introducing the rotated modulation and space-time-frequency component interleavers, the proposed scheme globally optimizes powerful forward error correction codes, rotated quadrature amplitude modulation, linear precoding MIMO, and OFDM, thus can achieve modulation diversity and space-time-frequency diversities as much as possible. A simple efficient optimal precoder selection criterion is put forward for this scheme. Based on the analysis of average mutual information, optimal rotation angles are given for different modulation and coding schemes, and the superiority of the proposed scheme is proved. Both software simulation and hardware prototype test results also verify that this new scheme can significantly outperform the conventional bit-interleaved coded modulation scheme under the non-ideal channel estimation, which is up to 4.5 dB signal-to-noise-ratio gain. In a word, the proposed scheme is a simple, efficient and robust transmission technique for the future MIMO---OFDM wireless systems.

Energy-Efficient Transmission Schedule for Delay-Limited Bursty Data Arrivals Under Nonideal Circuit Power Consumption

This paper develops a novel approach to obtain energy-efficient transmission schedules for delay-limited bursty data under nonideal circuit power consumption. Assuming a priori knowledge of packet arrivals, deadlines, and channel realizations, we show that the problem can be formulated as a convex program. For both time-invariant and time-varying fading channels, it is revealed that the optimal transmission between any two consecutive channel or data state changing instants, termed epoch, can only take one of the three strategies: i) no transmission; ii) transmission with an energy-efficiency (EE)-maximizing rate over part of the epoch; or iii) transmission with a rate greater than the EE-maximizing rate over the whole epoch. Based on this specific structure, efficient algorithms are then developed to find the optimal policies that minimize the total energy consumption with low complexity. The proposed approach can provide the optimal benchmarks for practical schemes designed for transmissions of delay-limited data arrivals and can be employed to develop efficient online scheduling schemes, which require only causal knowledge of data arrivals and deadline requirements.

On the Spectral Efficiency of Rate and Subcarrier Bandwidth Adaptive OFDM Systems Over Very Fast Fading Channels

In this paper, rate and subcarrier bandwidth adaptation (RSBA) on the average spectral efficiency of orthogonal frequency-division multiplexing (OFDM) systems using $M$ -ary quadrature amplitude modulation ( $M$ -QAM) is investigated in the presence of frequency-selective and very rapidly time-varying fading channels. The closed-form expressions for rate and capacity with perfect channel state information (CSI) and imperfect CSI are derived. In this paper, imperfect CSI is caused jointly by channel estimation error and unavoidable delay between when CSI is estimated and when the estimation results are used for actual transmission. The capacity with perfect CSI is just a special case of imperfect CSI. Based on the closed-form expressions of the maximum capacity, optimal RSBA algorithms with perfect and imperfect CSI are proposed, respectively. Theoretical and numerical results show that the RSBA scheme can improve the system performance effectively under the perfect-CSI case. It can make a tradeoff between intercarrier interference (ICI) and transmission efficiency by considering the cyclic prefix. The results also show that the RSBA scheme is effective in repelling the impact of outdated CSI, as well as in reducing the impact of channel estimation error, but to a lesser extent.

Kalman Filtering With Relays Over Wireless Fading Channels

This note studies the use of relays to improve the performance of Kalman filtering over packet dropping links. Packet reception probabilities are governed by time-varying fading channel gains, and the sensor and relay transmit powers. We consider situations with multiple sensors and relays, where each relay can either forward one of the sensors' measurements to the gateway/fusion center, or perform a simple linear network coding operation on some of the sensor measurements. Using an expected error covariance performance measure, we consider optimal and suboptimal methods for finding the best relay configuration, and power control problems for optimizing the Kalman filter performance. Our methods show that significant performance gains can be obtained through the use of relays, network coding and power control, with at least 30-40% less power consumption for a given expected error covariance specification.

Analysis of a Subset Selection Scheme for Wireless Sensor Networks in Time-Varying Fading Channels

One of the main challenges facing wireless sensor networks (WSNs) is the limited power resources available at small sensor nodes. It is therefore desired to reduce the power consumption of sensors while keeping the distortion between the source and its estimate at the fusion centre (FC) below a specific threshold. In this paper, we analyze a subset selection strategy to reduce the average transmission power of the WSN. We consider a two-hop network and assume the channels between the source and the relay sensors to be time-varying fading channels, modeled as Gilbert-Elliott channels. We show that when these channels are known at the FC, a subset of sensors can be selected by the FC to minimize transmit power while satisfying the distortion criterion. Through analysis, we derive the probability distribution of the size of this subset. We also consider practical aspects of implementing the proposed scheme, including channel estimation at relays. Through simulations, we compare the performance of the proposed scheme with schemes appearing in the literature. Simulation results confirm that for a certain range of end-to-end bit-error rates (BERs), the proposed scheme succeeds to achieve a superior power reduction compared to other schemes.

Robust signal recognition algorithm based on machine learning in heterogeneous networks

There are various heterogeneous networks for terminals to deliver a better quality of service. Signal system recognition and classification contribute a lot to the process. However, in low signal to noise ratio (SNR) circumstances or under time-varying multipath channels, the majority of the existing algorithms for signal recognition are already facing limitations. In this series, we present a robust signal recognition method based upon the original and latest updated version of the extreme learning machine (ELM) to help users to switch between networks. The ELM utilizes signal characteristics to distinguish systems. The superiority of this algorithm lies in the random choices of hidden nodes and in the fact that it determines the output weights analytically, which result in lower complexity. Theoretically, the algorithm tends to offer a good generalization performance at an extremely fast speed of learning. Moreover, we implement the GSM/WCDMA/LTE models in the Matlab environment by using the Simulink tools. The simulations reveal that the signals can be recognized successfully to achieve a 95% accuracy in a low SNR (0 dB) environment in the time-varying multipath Rayleigh fading channel.

Queue-Aware Energy-Efficient Joint Remote Radio Head Activation and Beamforming in Cloud Radio Access Networks

In this paper, we study the stochastic optimization of cloud radio access networks (C-RANs) by joint remote radio head (RRH) activation and beamforming in the downlink. Unlike most previous works that only consider a static optimization framework with full traffic buffers, we formulate a dynamic optimization problem by explicitly considering the effects of random traffic arrivals and time-varying channel fading. The stochastic formulation can quantify the tradeoff between power consumption and queuing delay. Leveraging on the Lyapunov optimization technique, the stochastic optimization problem can be transformed into a per-slot penalized weighted sum rate maximization problem, which is shown to be non-deterministic polynomial-time hard. Based on the equivalence between the penalized weighted sum rate maximization problem and the penalized weighted minimum mean square error (WMMSE) problem, the group sparse beamforming optimization based WMMSE algorithm and the relaxed integer programming based WMMSE algorithm are proposed to efficiently obtain the joint RRH activation and beamforming policy. Both algorithms can converge to a stationary solution with low-complexity and can be implemented in a parallel manner, thus they are highly scalable to large-scale C-RANs. In addition, these two proposed algorithms provide a flexible and efficient means to adjust the power-delay tradeoff on demand.

Proposal of channel estimation method for wireless two-way relay system of using SFBC MIMO-OFDM technique

In a two-way relay communication system, two user terminals (UTs) can communicate and exchange their information data through a relay station by using two timeslots. To realize the two-way relay communication system, each UT is required to estimate channel frequency responses (CFRs) both for up and down links in two timeslots efficiently which be employed in the demodulation of the other user's information data with frequency domain equalization. To satisfy this requirement, this paper proposes a novel CFR estimation method for the wireless two-way relay communication system of using SFBC MIMO-OFDM technique. The salient feature of proposed CFR estimation method is to employ the maximum likelihood estimation method for the proposed scattered pilot subcarriers assignment which can achieve higher CFR estimation accuracy even in higher time-varying fading channel and when the transmission OFDM signal is sampled by the non-Nyquist rate. In the proposed system, the SFBC technique is also employed for the data subcarriers both for the pilot symbols including data subcarriers and data symbols consisting of all data subcarriers in the frequency axis to improve the bit error rate (BER) performance in the two-way relay system. From the computer simulation results, this paper demonstrates the effectiveness of proposed two-way relay communication system of using SFBC MIMO-OFDM technique. To demonstrate the effectiveness of proposed two-way relay communication system of using SFBC MIMO-OFDM technique, this paper conducts various computer simulations as comparing with the conventional methods in higher time-varying fading channel. From the computer simulation results, this paper confirms that the proposed method even at the non-Nyquist rate can achieve higher channel estimation accuracy evaluated by the normalized mean square error (NMSE) and better BER performances by 5 and 22 times, respectively as comparing with the conventional methods when the normalized Doppler frequency ($$f_dT_S$$fdTS) is $$10^{-2}$$10-2 and the carrier to noise power ratio (C/N) is 25 dB.

Dynamic Optimization for Resource Allocation in Relay-Aided OFDMA Systems Under Multiservice

This paper investigates the dynamic resource allocation (RA) problem in cooperative OFDMA systems to maximize the average utility of all mobile stations (MSs) under different services. We propose a dynamic optimization framework for RA by considering three dynamic situations: time-varying fading channel, MSs' change of states, and relay stations (RSs)' change of states. Moreover, a dynamic RA algorithm based on discrete particle swarm optimization (DPSO) is proposed. The correlation between the adjacent frames is exploited to improve the performance of the dynamic RA algorithm. Simulation results show that the proposed dynamic algorithm achieves better performance at linear complexity, compared with the existing algorithms under different dynamic environments, while guaranteeing fairness to a proper level.

Transmission Schemes for Multicasting Hard Deadline Constrained Prioritized Data in Wireless Multimedia Streaming

In wireless multicast multimedia streaming, every data block (i.e., a group of packets) needs to be delivered within a hard deadline. On the other hand, to provide multilevel services, the widely adopted scalable video coding (SVC) prioritizes a video bit stream into a base layer and several enhancement layers. In this paper, we combine SVC with the transmission delay constraint and focus on multicasting hard deadline constrained prioritized (HDCP) data over wireless erasure channels. Specifically, we first define the performance metric and formulate the optimization problem. Then, we focus on a new adaptive RNC encoding and scheduling scheme to maximize the effective network throughput. Particularly, we propose simple and efficient greedy scheduling technique, which not only obtains near-optimal performance with low-time complexity but also suits time-varying fading channels. In addition, we extend our discussion to the more practical scenario with erroneous feedback and propose sampling-based feedback mechanism to reduce the system overhead. Both analytical and simulation results are provided to corroborate the effectiveness of the proposed techniques.

Detect-and-Forward Multirelay Systems With Decision-Feedback Differential Coherent Receivers

This paper considers a detect-and-forward multirelay wireless system employing differential MPSK modulation with decision-feedback differential coherent (DFDC) receivers. The DFDC receivers overcome the limitation of conventional differential detectors when used over time-varying fading channels and provide performance gains. Using a selective approach, the relays transmit only when the demodulation is errorless, and hence the destination employs an SNR-dependent threshold-decision rule to determine when the relays are active. The SNR-dependent thresholds ensure good performance over a wide SNR range. We propose the hold-and-estimate and hold-and-combine strategies for proper operation of the DFDC receivers over the relay to destination channels, to address the problem of intermittent transmissions on these links because of the selective protocol. We also demonstrate the necessity of initializing the DFDC receivers with pilot symbols. Finally, a recursive least squares adaptive algorithm is employed with the DFDC receivers to bypass the need of estimating the channel autocorrelation function. Analytical lower bounds to error probability illustrate the potential advantages of using DFDC receivers in such relaying systems. Extensive computer simulation results demonstrate the performance gains achieved by these relaying schemes with respect to comparable systems, especially over fast fading channels.

Design of pipeline R2MDC FFT for implementation of MIMO OFDM transceivers using FPGA

In this paper, an area-efficient low power Fast Fourier Transform (FFT) processor is proposed for Multi Input Multi Output--Orthogonal Frequency Division Multiplexing (MIMO-OFDM) that consists of a modified architecture of radix-2 algorithm which is described as Radix-2 multipath delay commutation (R2MDC). Orthogonal frequency-division multiplexing is a popular method for high-data-rate wireless transmission. OFDM may be combined with multiple antennas at both the access point and mobile terminal to increase diversity gain and/or Enhance system capacity on a time-varying multi path fading channel, resulting in a multiple-input multiple-output OFDM system. This paper describes the design of R2MDC FFT for implementation of MIMO OFDM transceiver using FPGA targeted to future wireless LAN systems. The proposed system is pipeline Radix 2multipath delay commutation FFT has been designed for MIMO OFDM. The MIMO OFDM transceivers have been designed according to the proposed OFDM parameters. A low-power efficient and full-pipeline architecture enables the real-time operations of MIMO OFDM transceivers. The FPGA board has been developed to verify their circuit behavior and implementation of MIMO OFDM Transceivers.

Design of MOD-R2MDC FFT for MIMO OFDM in wireless telecommunication system

In this paper, an area-efficient low power Fast Fourier Transform (FFT) processor is proposed for multi input multi output-orthogonal frequency division multiplexing (MIMO-OFDM) in wireless telecommunication system that consists of a modified architecture of radix-2 algorithm which is described as modified radix-2 multipath delay commutation (MOD-R2MDC). Orthogonal frequency-division multiplexing is a popular method for high-data-rate wireless transmission. OFDM may be combined with multiple antennas at both the access point and mobile terminal to increase diversity gain and/or enhance system capacity on a time-varying multi path fading channel, resulting in a multiple-input multiple-output OFDM system. This paper describes the VLSI design of an area efficient MOD-R2MDC FFT for MIMO OFDM system targeted to future wireless telecommunication LAN systems. The proposed system is pipeline modified radix 2 multipath delay commutation FFT has been designed for MIMO OFDM. A low-power efficient and full-pipeline architecture enables the real-time application of MIMO OFDM system.

Power Reduction of Variable Wordlength OFDM Receiver in Time-Varying Fading Channels by Monitoring Subcarrier SNRs

Determination of wordlength is essential for designing digital circuits because the wordlength affects system performance, hardware size, and power consumption. Variable wordlength methods that a system dynamically and effectively changes the wordlength depending on surrounding environments have been studied for power reduction in wireless systems. The conventional variable wordlength methods induce communication performance degradation when compared with a floating-point representation in time-varying fading channels. This paper discusses rapid wordlength control on packet basis and proposes a new method based on monitoring subcarrier SNRs in an OFDM receiver. The proposed method can estimate signal quality accurately and can decrease the wordlength decision errors. The simulation results have indicated that the proposed method shows better PER performance compared with the conventional methods.

Power and Rate Adaptation Based on CSI and Velocity Variation for OFDM Systems Under Doubly Selective Fading Channels

In this paper, a novel joint continuous power and rate adaptation scheme is proposed fordoubly selective fading channels in orthogonal frequency division multiplexing (OFDM) systems, based on terminal velocity and perfect or imperfect channel state information (CSI). The analysis and simulation results show that the continuous power and rate adaptation scheme is very effective and improve the performance of OFDM systems substantially under time-varying fading channels, as compared with the traditional adaptation schemes operating without a priori knowledge of velocity and mobility adaptation without CSI.

Applications of Capacity Limits to Performance Analyses of Adaptive Transmission Protocols for Packet Radios

Analytical methods are provided for use in performance evaluations, tradeoff studies, and preliminary designs of adaptive modulation and coding protocols that obtain their control information from practical sources. Our approach employs capacity limits and Markov chain models of fading to give analytical results on the throughput achieved by adaptive transmission in packet radio systems. The analytical methods replace simulations of the modem, iterative decoder, and time-varying fading channel. The amount of processor time required for protocol performance evaluations is decreased by several orders of magnitude.

Performance Analysis of the STBC System in a Time-Varying Channel

In this paper, we analyze the performance of STBC system with two transmit antennas in a varying channel environment. STBC system designed to channel environment is quasi still was confirmed that the performance degradation in a time-varying fading channel. Thus it was applied to the detection method using an equalizing method to improve the performance. ZF according to the simulation result and the channel correlation coefficient applying the techniques MMSR performance degradation, but was confirmed SNR gain than conventional detection technique is 5dB or more improvements are possible. Taking out the group of stone to be removed by the connected point, the pattern value for the removal of stones platen pattern adjustment program that implements the notation displayed immediately.