Shouyi Yang

Decision-directed channel estimation based on iterative linear minimum mean square error for orthogonal frequency division multiplexing systems

A decision-directed (DD) channel estimation based on iterative linear minimum mean square error (LMMSE) is proposed for orthogonal frequency division multiplexing systems. Existing DD channel estimation is well known to have the problem of error propagation because of symbol-by-symbol detection. The proposed algorithm can estimate the correction term of current channel state information (CSI) according to the error vector of previous CSI by applying the orthogonality principle, and corrects the current CSI with this correction term. Analysis and simulation results have shown that this method has no error propagation problem. The performance of the proposed algorithm is much better than the conventional DD channel estimation, and close to the optimal LMMSE estimator, but with much less computational complexity compared with the optimal LMMSE estimator.

Dynamic Spatial Subcarrier and Power Allocation for Multiuser MIMO-OFDM System

The adaptive antenna-array based OFDM system always uses beamforming to choose the channel with largest Eigenvalue to transmit the OFDM block symbol. Such selection diversity is a simple way. However, it does not make full use of the capacity antenna-array promise. With the goal of maximizing the system throughput with a limited power for the target BER, a novel dynamic subcarrier and power allocation scheme based on SVD decomposition is proposed in this paper. We investigate the algorithm in three backgrounds: the impact of SNR, antenna number and user number. Numerical simulation results show that the proposed subcarrier and power assigning algorithm yields a much larger multiplexing gain than the largest Eigen model.

Multi-channel power allocation based on market competitive equilibrium in cognitive radio networks

Cognitive radios such as intelligent phones and Bluetooth devices have been considered essential goods in next-generation communication systems. Such devices will have to share the same frequency band owing to the limited bandwidth resource. To improve spectrum efficiency, we formulate multi-channel power allocation as a market competitive equilibrium (CE) problem, and prove that its solution exists and is unique under the condition of weak interference. We then propose two distributed power allocation algorithms achieving CE, namely the fast convergent power allocation algorithm (FCPAA) and the social-fairness-aware FCPAA (SFAF). Theoretical analysis and simulation results demonstrate that the proposed algorithms lead to better system performance in terms of the guaranteed interference temperature constraint using the price mechanism instead of a strategy based on the Nash equilibrium. Moreover, it is shown that the FCPAA maximizes total utility, and converges more quickly than the method addressed in prior research with the help of improved round-robin rules. However, the FCPAA cannot ensure the same social fairness among secondary users as the SFAF scheme in both the non-fading channel and Rayleigh fading channel; the SFAF balances the individual utility by adjusting each user’s budget at the expense of a small quantity of system total throughput.

Adaptive spectrum access strategies in the context of spectrum fragmentation in cognitive radio networks

Because of the presence of incumbents in cognitive radio networks, the unused spectrum in the TV bands, popularly referred to as ‘white spaces’, are fragmented with the size of each fragment varying from one TV channel to several TV channels. What is more, because the secondary transmissions adjust their spectrum usage over time, white spaces become increasingly partitioned into a collection of discrete fragments, which decreases the spectral utilization. To improve throughputs, most of the prior researches focused on selecting the best transmission channel in the context of spectrum fragmentation but have rarely involved aggregating the fragmentation to a contiguous channel. In this paper, we present two adaptive spectrum access strategies, both of which not only select the best transmission channel but also efficiently solve the fragmentation problem. The first strategy involves one‐agile radios that build a transmission using single fragment of frequency, which partially remedy the fragmentation problem using higher‐layer solutions. The second strategy suppresses the impact of spectrum fragmentation successfully at the physical layer by combining k spectrum fragments to form a single transmission. The simulation results show that both of the strategies bring larger throughputs compared with the prior solutions. Copyright

Market competition-based joint resource allocation in primary and cognitive radio networks

In this paper, we study the problem of jointing power and rate optimization in multi-channel Heterogeneous Cognitive Radio Networks (H-CRNs), where the Leader-Follower relationship between Primary Users (PUs) in macrocells and Secondary Users (SUs) in femtocells is modeled as a Stackelberg game. We formulate the problem of power allocation in primary networks as a Non-Cooperative Game, while formulating the jointing power and rate optimization in cognitive networks as a Market Competition Equilibrium problem. Furthermore, we propose a Primary networks and Cognitive networks Joint Resource Allocation (PCJRA) algorithm to maximize the utilities of SUs subject to the maximum rate requirements for PUs. Theoretical analysis and simulation results demonstrate both the feasibility of the multi-channel H-CRNs model and the effectiveness of the proposed PCJRA algorithm.

Modeling spectrum access strategies in cognitive radio networks using Colored Petri Nets

The spectrum access strategy is one of the important design aspects for better system capacity in cognitive radio networks (CRN), which is characterized as complex and concurrent access processing of multiple users. The common approach modeling spectrum access is Markov Chain (MC), which is prone to state space explosion with the increasing of the number of users. In this paper, an executable hierarchical Colored Petri Nets (CPN) model for the spectrum access in CRN is investigated to overcome the explicit limitation using MC. After the verification that the CPN model is isomorphic to MC in the case of arriving with Poisson distribution, the advantage of CPN on computation complexity is analyzed. Finally, a spectrum access strategy with queuing for the secondary users is proposed and modeled by CPN, which is demonstrated more flexible and workable than MC by the results.

An novel ML estimator based on the Lagrange interpolation for the OFDM systems

Existing maximum likelihood (ML) channel estimation in orthogonal frequency division multiplexing (OFDM) systems requires knowledge of the effective length of the channel impulse response (CIR) to achieve the optimum performance. But it is very difficult to track effective length of the CIR in a practical system. By analyzing the relation between the performance of the ML estimation and the exactness of the CIR effective length estimation, we propose a novel ML channel estimator which combine the ML estimation with the successive approximation based on Lagrange interpolation polynomial and can track the variation of the effective length of CIR more easily. Simulation results show that the proposed ML channel estimation algorithm can provide nearly the same performance as the conventional ML channel estimation with the actual length of CIR.

On the performance of Alamouti-based OFDM system with multiuser resource allocation and scheduling

Efficient resource management has been a very appealing issue in the operation of wireless communication system. With the goal of minimizing the total transmit power, we mainly discussed the constant-bit-rate (CBR) case for multiuser MIMO-OFDM system, and developed a novel dynamic subcarrier allocation criteria based on Alamouti scheme with a tradeoff between the complexity of implementation and BER performance against eigen beamforming. The proposed scheme, including antenna selection, dynamic subcarrier assignment among users and adaptive bit loading, can acquire transmitting/receiving diversity and multiuser diversity simultaneously. Simulations showed that the given scheme can optimize the system BER performance.