To improve the performance of the optimal pilot sequences over multiple OFDM symbols in fast time-varying channels, this letter proposes a novel channel estimation method using virtual pilot tones in multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. Assuming that the superimposed virtual pilot tones at the data locations over the specific sub-carriers are transmitted from all transmit antennas, the corresponding virtual received pilot signals at the same locations are obtained from the neighboring real received pilot signals over the same sub-carriers by Wiener filter. Based on the least squares (LS) channel estimation, the channel parameters can be obtained from the combination of the virtual and real received pilot signals over one OFDM symbol. Simulation results show that the proposed channel estimation method greatly outperforms the previous method for the optimal pilot sequences over multiple OFDM symbols in fast time-varying channels, as well as approaches the method for the comb-type optimal pilot sequences in performance.

Iterative receivers, which perform MMSE detection and decoding iteratively, can provide significant performance improvement compared with noniterative method. However, due to the high computational cost and numerical instability, conventional MMSE detection using a priori information can not be implemented in hardware. In this letter, we propose a newly-built iterative receiver which is division-free and numerically stable, and then we analyze the results of a fixed-point simulation and present the hardware implementation architecture.

Multiuser diversity, identified by recent information theoretic results, is a form of diversity inherent in a wireless network. The diversity gain is obtained from independent time-varying fading channels across different users. The main practical issue in multiuser diversity is lack of Quality of Service (QoS) guarantees. This study proposes a wireless scheduling algorithm named MUDSEQ for downlink channels exploiting multiuser diversity under explicit QoS constraints. The numerical results demonstrate that the novel algorithm can yield non-negligible diversity gain even under tight QoS constraints and little scattering or slow fading environments. Additionally, a system framework for dynamic resource allocation based on the proposed algorithm is developed.

We use network coding based on coded cooperation for the Two-Way Relay channel, where two nodes communicate with each other assisted by a third, relay node. We consider the time-division two-way relay channel without power control, which means the two users and the relay use the same transmission power. Using the proposed network coding approach, channel codes are used at both users and network coding is used at the relay. It is shown via simulation that the proposed scheme provides substantial coding gain in fading channels.

In this paper, we propose an ICI mitigation method for MIMO OFDM using turbo detection technique. In order to reduce the computational complexity, we present a method for dividing the received frequency-domain signals into subbands and the manner of division varies with each iteration, joint soft ICI cancellation and decoding is then performed on each subband. To perform iterative ICI mitigation, the estimation of the time-variant channel using a great quantity of pilot tones is needed, which results in poor spectral efficiency. We then propose a method to reduce the required scatter pilot tones, which is differentially-modulated-pilot scheme. Moreover, the estimation can be constructed based on EM-type algorithms to further reduce the computational complexity. Finally, the results of computer simulations demonstrate that the proposal can provide significant performance improvement.

This paper addresses the problem of channel estimation for multiple-input and multiple-output orthogonal frequency division multiplexing (MIMO-OFDM)-based wireless networks with frequency-reuse. Firstly, the optimal time-domain training sequences are derived for the multiple cells with the same frequency group and a set of suitable sequences are also presented for practical implementation. Secondly, a low complexity iterative algorithm is combined with the time domain channel estimation to suppress the co-channel interferences (CCIs). The channel estimation method is applied to synchronous and asynchronous cellular and the MSE performance of the estimator is also analyzed. Simulation results demonstrate that the presented channel estimation approach can substantially suppress CCIs and outperform the conventional LS MIMO-OFDM channel estimation over multipath fading channels in multicell environments.

In this letter, we study cooperative transmission in wireless multicast networks. An opportunistic cooperative multicast scheme based on coded cooperation (OCM-CC) is proposed and its closed-form expression of outage performance is obtained. Through numeric evaluation, we analyze its outage probability with different numbers of relays and different cooperative ratios.

In this letter, we focus on a system where N sources send n ≤ N different packets to one destination, through M ≥ N relays. Each relay employs random linear network coding to encode the packets it received by randomly choosing coefficients in a finite field Fq, then forwards it to the destination. Owing to the inherent errorprone nature of erasure channels, data packets received by the relay and the destination nodes may not be correct. We analyze the optimal throughput with respect to n, given a series of parameters and derive the upper and lower bounds of throughput performance. We also analyze the impact of the number of relays and the erasure probability on the throughput performance. Simulation results are well matched with the theoretical analysis.

This letter investigates the outage performance of a joint transmit and receive antenna selection scheme in an amplify-and-forward two-way relaying system with channel estimation error. A closed-form approximate outage probability expression is derived, based on which the asymptotic outage probability expression is derived to get an insight on system's outage performance at high signal-to-noise (SNR) region. Monte Carlo simulation results are presented to verify the analytical results.

One major challenge to implement orthogonal frequency division multiplexing (OFDM) systems over doubly selective channels is the non-negligible intercarrier interference (ICI), which significantly degrades the system performance. Existing solutions to cope with ICI include zero-forcing (ZF), minimum mean square error (MMSE) and other linear or nonlinear equalization methods. However, these schemes fail to achieve a satisfactory tradeoff between performance and computational complexity. To address this problem, in this paper we propose two novel nonlinear ICI cancellation techniques, which are referred to as parallel interference cancelation (PIC) and hybrid interference cancelation (HIC). Taking advantage of the special structure of basis expansion model (BEM) based channel matrices, our proposed schemes enjoy low computational complexity and are capable of cancelling ICI effectively. Moreover, since the proposed schemes can flexibly select different basis functions and be independent of the channel statistics, they are applicable to practical OFDM based systems such as DVB-T2 over doubly selective channels. Theoretical analysis and simulation results both confirm their performance-complexity advantages in comparison with some existing methods.

A simple yet effective time domain correlation channel estimation method is proposed for multiple-input multiple-output (MIMO) systems over dispersive channels. It is known that the inherent co-channel interference (CCI) and inter-symbol interference (ISI) coexist when the signals propagate through MIMO frequency selective channels, which renders the MIMO channel estimation intractable. By elaborately devising the quasi-orthogonal training sequences between multiple antennas which have constant autocorrelation property with different cyclic shifts in the time domain, the interferences induced by ISI and CCI can be simultaneously maintained at a constant and identical value under quasi-static channels. As a consequence, it is advisable to implement the joint ISI and CCI cancelation by solving the constructed linear equation on the basis of the correlation output with optional correlation window. Finally, a general and simplified closed-form expression of the estimated channel impulse response can be acquired without matrix inversion. Additionally, the layered space-time (LST) minimum mean square error (MMSE) (LST-MMSE) frequency domain equalization is briefly described. We also provide some meaningful discussions on the beginning index of the variable correlation window and on the cyclic shift number of m-sequence of other antennas relative to the first antenna. Simulation results demonstrate that the proposed channel estimation approach apparently outperforms the existing schemes with a remarkable reduction in computational complexity.

This paper presents an iterative algorithm for decoding product codes based on syndrome decoding of component codes. This algorithm is devised to achieve an effective trade-off between error performance and decoding complexity. A simplified list decoding algorithm, which uses a modified syndrome decoding method, for linear block codes is devised to deliver soft outputs for iterative decoding of product codes. By adjusting the size of the list, the decoder can achieve a proper trade-off between decoding complexity and performance. Compared to the other iterative decoding algorithms for product codes, the proposed algorithm has lower complexity while offers at least the same performance, which is demonstrated by analyses and simulations. The proposed algorithm has been simulated for BPSK and 16-QAM modulations over both the additive white Gaussian noise (AWGN) and Raleigh fading channels. This paper also presents an efficient scheme for applying product codes and their punctured versions. This scheme can be implemented with variable packet size and channel data block.

This paper addresses the downlink transmission strategies with dynamic resource allocation for multiuser MIMO-OFDM systems. The ultimate objective is to maximize the sum rate capacity subject to average power constraints. Considering that the performance of conventional Orthogonal Frequency Division Multiple Access (OFDMA) is limited by users' exclusive use to subcarrier, while Dirty Paper Coding (DPC) is capable of supporting multiple users, we propose joint subcarrier and power allocation and precoding schemes based on OFDMA combined with DPC, which is called DPC-OFDMA. The analysis is considered in two stages with channel state information (CSI) at transmitter. The first stage applies water-filling method to address subcarriers allocation, in which users are allowable to share subcarriers. The second stage employs DPC combined with precoding to deal with simultaneous transmissions of the users sharing the same subcarriers. An efficient algorithm to choose the best possible ordering of users for DPC and the optimal precoding design of each user are also involved. To reduce the complexity for practice, two simplified strategies are proposed. One is called suboptimal DPC-OFDMA, where the number of users using the same subcarrier is restricted. Another employs beamforming (BF) at every subcarrier referred as BF-DPC-OFDMA. Simulation results show that the proposed simplified strategies can approach the optimal performance for most cases, and have higher spectral efficiency than conventional time-sharing OFDMA.

The traditional spectrum auctions require a central auctioneer. Then, the secondary users (SUs) can bid for spectrum in multiple auction or sealed auction way. In this paper, we address the problem of distributed spectrum sharing in the cognitive networks where multiple owners sell their spare bands to multiple SUs. Each SU equips multi-interface/multi-radio, so that SU can buy spare bands from multiple owners. On the other hand, each owner can sell its spare bands to serval SUs. There are two questions to be addressed for such an environment: the first one is how to select bands/the owners for each SU; the second one is how to decide the competitive prices for the multiple owners and multiple SUs. To this end, we propose a two-side multi-band market game theoretic framework to jointly consider the benefits of all SUs and owners. The equilibrium concept in such games is named core. The outcomes in the core of the game cannot be improved upon by any subset of players. These outcomes correspond exactly to the price-lists that competitively balance the benefits of all SUs and owners. We show that the core in our model is always non-empty. When the measurement of price takes discrete value, the core of the game is defined as discrete core. The Dynamic Multi-band Sharing algorithm (DMS) is proposed to converge to the discrete core of the game. With small enough measurement unit of price, the algorithm can achieve the optimal performance compared with centralized one in terms of the system utility.

Cognitive radio is a promising approach to ensuring the coexistence of heterogeneous wireless networks since it can perceive wireless conditions and freely switch among different network modes. When there are many network opportunities, how to decide the appropriate network selection for CR user's current service is the main problem we study in this paper. We make full use of the intelligent characteristic of CR user and propose a fuzzy learning based network selection scheme, in which the network selection choice is made based on the estimated evaluations of available networks. Multiple factors are considered when estimating these evaluations. Both the outer environment factors directly sensed by CR user (signal strength of the available network and network mode), and also the factor that cannot be determined beforehand and is learnt by our scheme (the bandwidth allocated by the optional network) are considered. From several interactions with the wireless environment, the experience of network selection behavior is accumulated which will direct our scheme to make a proper decision of the network. Two simulations verify that our scheme could not only guarantee a better bandwidth requirement of CR user compared with other three network selection methods, but also shows it to be a reasonable scheme for utilizing the available resources of these networks.

In this paper, we investigate the effect of outdated channel state information (CSI) on decode-and-forward opportunistic mobile relaying networks with direct link (DL) between source node and destination node. Relay selection schemes with different levels of CSI are considered: 1) only outdated CSI is available during the relay selection procedure; 2) not only outdated CSI but also second-order statistics information are available in relay selection process. Three relay selection schemes are proposed based on the two levels of outdated CSI. Closed-form expressions of the outage probability are derived for the proposed relay selection schemes. Meanwhile, the asymptotic behavior and the achievable diversity of three relay selection schemes are analyzed. Finally, simulation results are presented to verify our analytical results.

We consider the problem of transmit power and bit rate allocation for OFDM based cognitive radio systems. An efficient allocation algorithm which mainly consists of two steps is proposed to maximize the sum rate of secondary users. In the first step of the algorithm, original nonlinear problem is converted to a convex problem which is solved by dual methods, and in the second step the final resource allocation results is obtained via iterative power rescale operation. Numerical results show the effectiveness of the proposed algorithm.

A novel and energy-efficient algorithm with Quality-of-Service (QoS) guarantee is proposed for cooperative spectrum sensing (CSS) with soft information fusion and hard information fusion. By weighting the sensing performance and the consumption of system resources in a utility function that is maximized with respect to the number of secondary users (SUs), it is shown that the optimal number of SUs is related to the price of these QoS requirements.

A multi-user space-time block coding (STBCa) system is a multi-access system where co-channel users employ space-time block codes (STBC). In this paper, we aimed at the design of efficient zero-forcing (ZF) receivers, especially ZF iterative interference cancellation (IC) receivers, for multi-user {G2, G3, G4} STBC systems with an arbitrary number of users, based on the identification of algebraic properties existing in the systems. First, we identify some algebraic properties for {G2, G3, G4} STBC systems. Then, utilizing these algebraic properties, we further expose two significative properties, called "ZF output uncorrelated property" and "ZF output equal Post-detection SNR property" respectively, for least-squares (LS) ZF receivers in multi-user {G2, G3, G4} STBC systems by detailed proofs. Based on the two properties, a novel LS ZF user-ordered successive interference cancellation (ZF UOSIC) detection algorithm is proposed subsequently. Finally, simulation results show that ZF UOSIC is superior to the conventional ZF IC and maximum-likelihood (ML) algorithms and the non-ordered ZF user-based SIC (ZF USIC) algorithm due to adopting iterative IC and optimal ordering among users, and has very close performance to the ZF symbol-ordered SIC but with lower complexity due to the fewer iterative times.