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This paper proposes a simple method to enlarge the estimation range of conventional carrier frequency offset (CFO) estimation methods based on correlations among the identical parts of the preamble. A novel preamble is designed, which is composed of one regular OFDM training block with even numbers of identical parts and one irregular OFDM training block with odd numbers of identical parts. The initial estimates obtained over the two training blocks are next exploited to jointly estimate the CFO. By elaborately selecting the numbers of identical parts for the two training blocks, the proposed CFO estimator can estimate frequency offset over tens of the subcarrier spacing. Simulation results showed that the proposed CFO estimator satisfies the estimate range requirement for the practical OFDM systems, while achieving a very good estimate performance.

Considering that channel estimation plays a crucial role in coherent detection, this paper addresses a method of Recursive-least-squares (RLS) channel estimation with adaptive forgetting factor in wireless space-time coded multiple-input and multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. Because there are three different forgetting factor scenarios including adaptive, two-step and conventional ones applied to RLS channel estimation, this paper describes the principle of RLS channel estimation and analyzes the impact of different forgetting factor scenarios on the performances of RLS channel estimation. Simulation results proved that the RLS algorithm with adaptive forgetting factor (RLS-A) outperformed that with two-step forgetting factor (RLS-T) or with conventional forgetting factor (RLS-C) in both estimation accuracy and robustness over the multiple-input multiple-output (MIMO) channel, i.e., a wide-sense stationary uncorrelated scattering (WSSUS) and frequency-selective slowly fading channel. Hence, we can employ the RLS-A method by adjusting forgetting factor adaptively to track and estimate channel state parameters successfully in space-time coded MIMO-OFDM systems.

Differential space-time coding was proposed recently in the literature for multi-antenna systems, where neither the transmitter nor the receiver knows the fading coefficients. Among existing schemes, double differential space-time (DDST) coding is of special interest because it is applicable to continuous fast time-varying channels. However, it is less effective in frequency-selective fading channels. This paper’ls authors derived a novel time-frequency double differential space-time (TF-DDST) coding scheme for multi-antenna orthogonal frequency division multiplexing (OFDM) systems in a time-varying frequency-selective fading environment, where double differential space-time coding is introduced into both time domain and frequency domain. Our proposed TF-DDST-OFDM system has a low-complexity non-coherent decoding scheme and is robust for time-and frequency-selective Rayleigh fading. In this paper, we also propose the use of state-of-the-art low-density parity-check (LDPC) code in serial concatenation with our TF-DDST scheme as a channel code. Simulations revealed that the LDPC based TF-DDST OFDM system has low decoding complexity and relatively better performance.

In this letter, the limited feedback scheme in MIMO-Relay systems is considered. We propose a new strategy that optimizes the allocation of feedback bits between channel direction information (CDI) and phase information (PI) for multi-relay systems under the total number of feedback bits constraint. The proposed scheme eventually trades off some CDI bits for PI feedback to diminish the phase ambiguity. Simulation results show that compared to the conventional and the 1-bit PI feedback methods, the proposed scheme remarkably improves the system performance without increasing the feedback overhead.

International audience; Prenatal caffeine exposure (PCE) alters the hypothalamic-pituitary-adrenocortical (HPA) axis-associated neuroendocrine metabolic programming and induces an increased susceptibility to metabolic syndrome (MS) in intrauterine growth retardation (IUGR) offspring rats. High-fat diet (HFD) is one of the main environmental factors accounting for the incidence of MS. In this study, we aimed to clarify the gender-specific increase in susceptibility to MS in offspring rats after PCE with post-weaning HFD. Maternal Wistar rats were administered with caffeine (120 mg/kg.d) from gestational day 11 until delivery. The offspring rats with normal diet or HFD were euthanized at postnatal week 24, and blood samples were collected. Results showed that PCE not only reduced serum adrenocorticotropic hormone (ACTH) and corticosterone levels, but also enhanced serum glucose, triglyceride and total cholesterol (TCH) concentrations in the offspring rats. Moreover, several interactions among PCE, HFD and gender were observed by a three-way ANOVA analysis. In PCE offspring, HFD could aggravate the degree of increased serum triglyceride level. Meanwhile, serum corticosterone levels of females were decreased more obviously than those of males in PCE offspring. The results also revealed interactions between HFD and gender in the levels of serum ACTH, triglyceride and TCH, which were changed more evidently in female HFD offspring. These results indicate that HFD could exacerbate the dysfunction of lipid metabolism and the susceptibility to MS induced by PCE, and the female offspring are more sensitive to HFD-induced neuroendocrine metabolic dysfunction than their male counterparts. (C) 2015 Elsevier Inc. All rights reserved.

To further improve spectrum efficiency, small cell is regarded as a promising approach by the Third Generation Partnership Project (3GPP) framework. However, when small cells are co-channel deployed with macro cells, interference is an inevitable problem and severely restricts the system performance. In order to maximize the offloading benefits of small cells and mitigate the interference from the macro cell tier to the small cell tier, cell range expansion (CRE) and almost blank subframes (ABS) have been designed for small cells and macro cells, respectively. In this paper, a reference signal received quality (RSRQ) based offloading strategy is investigated. Based on bursty traffic load, each macro cell decides its ABS pattern distributedly. Moreover, a new scheduling policy is proposed to deal with staggered ABS patterns in adjacent macro cells. System-level simulation results could verify that compared with traditional fixed CRE bias and ABS operations, our proposed scheme can achieve superior performance gains in terms of downlink (DL) and uplink (UL) packet throughput.

The hypothalamic-pituitary-adrenal (HPA) axis is one of the most important neuroendocrine axes and plays an important role in stress defense responses before and after birth. Prenatal exposure to xenobiotics, including environmental toxins (such as smoke, sulfur dioxide and carbon monoxide), drugs (such as synthetic glucocorticoids), and foods and beverage categories (such as ethanol and caffeine), affects fetal development indirectly by changing the maternal status or damaging the placenta. Certain xenobiotics (such as caffeine, ethanol and dexamethasone) may also affect the fetus directly by crossing the placenta into the fetus due to their lipophilic properties and lower molecular weights. All of these factors probably result in intrauterine programming alteration of the HPA axis, which showed a low basal activity but hypersensitivity to chronic stress. These alterations will, therefore, increase the susceptibility to adult neuropsychiatric (such as depression and schizophrenia) and metabolic diseases (such as hypertension, diabetes and non-alcoholic fatty liver disease). The "over-exposure of fetuses to maternal glucocorticoids" may be the main initiation factor by which the fetal HPA axis programming is altered. Meantime, xenobiotics can directly induce abnormal epigenetic modifications and expression on the important fetal genes (such as hippocampal glucocorticoid receptor, adrenal steroidogenic acute regulatory protein, et al) or damage by in situ oxidative metabolism of fetal adrenals, which may also be contributed to the programming alteration of fetal HPA axis.

This letter investigates a subchannel and power allocation (SPA) algorithm which maximizes the throughput of a user under the constraints of total transmit power and fair subchannel occupation among relay nodes. The proposed algorithm reduces computational complexity from exponential to linear in the number of subchannels at the expense of a small performance loss.

In recent years, there is a significant trend for VANET to provide not only traditional services like warning information exchanging for road safety and car collision avoidance but also various multimedia applications such as mobile TV which may require broadband access to core network or Internet. On the other hand, service provision technologies with point-to-multipoint transmission mode which could better utilize the limited wireless resource have been well discussed and standardized, such as MBMS in 3GPP and BCMCS in 3GPP2. In this paper, we propose an effective solution aimed to enable multicast/broadcast service provision in integrated VANET-cellular heterogeneous wireless networks based on a two-phase cooperative transmission strategy. Through analysis and simulation, our proposal combines advantages of these two heterogeneous networks and the nature of multicast/broadcast technology.

D2D (Device-to-Device) communication underlaying cellular networks will become a significant technology in the future to decrease the load of base station (BS) and improve the overall spectral efficiency. However, mutual interference will be brought out when D2D communication reuses the resource of cellular communication. System performance may be degraded a lot when severe interference has not been controlled. In this paper, we propose an efficient interference coordination mechanism for D2D communication, which is based on resource allocation by reasonably selecting cellular resources and controlling transmit power for D2D communication links. The proposed mechanism can increase the number of reliable D2D communication links in system while prioritizing cellular uplink communication. Simulation results show the efficiency of our proposed scheme.

Wireless devices have experienced great development in the past decade. During this period, secrecy studies have drawn heated attention. Traditionally, there mainly exist two methods to optimize secrecy transmissions, precoding scheme and artificial-noise-aided scheme. In this paper, we propose a joint design of precoding and artificial noise in a relay-aided network with the channel state information (CSI) already known. Besides, based on wiretapping knowledge known or not, defined by whether we have known which user is wiretapped, we proposed two different schemes. Simulation results are given to verify the effectiveness of our proposed schemes.

This paper studies the precoder design of a multi-relay multi-user bidirectional networks in which each relay is equipped with multiple antennas. We study the relay precoder design in the case of imperfect channel state information (CSI) and a norm-bounded error model is adopted. Then, we solve the power minimization problem under this scenario. Numerical results demonstrate that the proposed robust precoding algorithm outperforms the non-robust solution.

The heterogeneous multicast networks are the networks with several wireless technologies that provide multicast service. Due to the high data rate of the service, point-to-point (P2P) transmission mode, which is employed by unicast channels, is no longer the best mode because of its inefficiency in power consumption and spectrum utilization. Compared with P2P, point-to-multipoint (P2M) transmission mode is recognized as a more promising mode for multicast service. But since P2M mode is provided by mulitcast channels who have turn-on thresholds, the P2M link of a transmission point (TP) is not always available for User Equipments (UEs). To deal with the UEs' cell/transmission mode selection problem in heterogeneous multicast networks, this paper proposes a novel auction mechanism. In the auction process, TPs act as auctioneers who own channel resource and UEs act as bidders who wish to buy these channels for multicast service. Different from many auction based mechanism, we design two kinds of prices, one for unicast channels providing P2P links and the other for multicast channels providing P2M links. In auction, the equilibrium is defined as the state that no UE wishes to change it decision. Through simulation, we show that the auction process converges to a equilibrium state, and the mechanism achieves about 40%-50% power efficiency compared with that of random access.

In this chapter, we address the common feedback framework (CFF) for downlink coordinated multipoint (CoMP) transmissions in Long-Term Evolution (LTE) Release 11 networks. First, we introduce the work item of CoMP in LTE Release 11 and the ambitious goal of standardizing a CFF to support all interested CoMP schemes. Second, we discuss four candidates of CFF options, with the emphases on feedbacks of co-phase information (CFF option 2) and aggregated CQI (CFF option 3). From system-level simulation results, it can be observed that both CFF options 2 and 3 are able to offer considerable cell-edge throughput gains compared with the non-CoMP scheme. Third, we review the relevant standardization activities and explain why it is another CFF option that will eventually be adopted in LTE Release 11. Finally, some concluding remarks are provided to forecast the further development of CoMP CFF in the future.

In this chapter, the application of multipoint cooperative communication in the 4G networks, that is, the coordinated multipoint (CoMP) system, is addressed from a variety of aspects. First, we review the development of CoMP in the standardization of Long-Term Evolution-Advanced (LTE-A) networks and analyze the reason of its preclusion from the LTE Release 10 specification. Second, we discuss the renewed campaign of CoMP in LTE Release 11, including the downlink transmission and uplink reception schemes of CoMP, as well as the related specification works. Third, we analyze the simulation results from the 3GPP CoMP study item to show the advantages of CoMP system in practical cellular networks.

For the seventh category of multipoint cooperative communication technology, we investigate the interference coordination schemes for the uplink frequency division multiple access (FDMA) cellular network in this chapter. First, we elaborate on the topology of a cellular system and show the interference problem in the uplink FDMA network. Second, we discuss the hard, fractional, and soft frequency reuse schemes, and then we address our motivations to improve the static implementation of soft resource reuse scheme with minimum intercell CSI exchanges. Third, we propose an advanced interference coordination scheme that consists of six steps with the key design lying in the enhanced user equipment (UE) categorization and resource-access control policies. In order to verify the effectiveness of the proposed scheme, we resort to the approach of system-level simulation, the methodology and implementation of which are addressed in great details. From the simulation results, it can be observed that compared with the conventional schemes, the proposed scheme can largely increase the efficiency of the trade-off between the cell-edge throughput and the overall throughput, thus showing high values in the study of interference coordination and application for the uplink FDMA cellular network.

For the eighth category of multipoint cooperative communication technology, we discuss joint precoding schemes with ideal backhaul conditions for the downlink cellular network in this chapter. First, we introduce some of the well-known precoding schemes for joint transmission (JT), that is, the global precoding (GP), local precoding (LP), weighted local precoding (WLP), and single-frequency network precoding (SFNP) schemes. Second, we propose an enhanced SFNP scheme with smart antenna selection (AS) operated at the cooperating base stations (BSs), which is named AS-SFNP scheme. Third, for single-antenna UEs, both analytical lower bounds and simulation results are provided to show that both the proposed AS-SFNP scheme and the WLP scheme achieve performance close to that of the optimal GP scheme in terms of average signal-to-interference-plus-noise ratio (SINR). For multi-antenna UEs, simulation results demonstrate that the proposed AS-SFNP scheme can achieve a larger capacity than the LP, WLP, and SFNP schemes in high-SNR regime. Furthermore, from a system-level simulation of a practical cellular network, the AS-SFNP scheme with a low feedback overhead and low-complexity implementation shows comparable performance of the cell-edge spectral efficiency with the WLP and GP schemes.

For the eighth category of multipoint cooperative communication technology, we discuss the sequential and incremental precoding scheme with nonideal backhaul conditions for the downlink joint transmission (JT) network in this chapter. First, we address the system model of JT and describe the backhaul impairments. Second, we discuss the conventional autonomous global precoding (AGP) scheme, which may suffer from severe performance degradation in the event of partial JT and single-BS transmission (ST) resulted from imperfect backhaul communications. Third, we propose a sequential and incremental precoding (SIP) scheme to overcome the drawbacks of the existing schemes. The objective of our design is to minimize the maximum of the sub-stream mean square errors (MSE), which dominates the average bit error rate (BER) performance of the system. The key problem is first illustrated and solved with a two-BS JT system, and the results are then generalized to multi-BS JT systems. Simulations show that, under the practical backhaul link conditions, our scheme significantly outperforms the AGP scheme in terms of BER performance.

For the sixth category of multipoint cooperative communication technology, we address the relay/antenna selection schemes for the amplify-and-forward (AF) multiple-input multiple-output (MIMO) relay network in this chapter. First, we discuss the system model of an AF MIMO relay network as well as the value of relay/antenna selection when joint relay precoding cannot be operated. Second, we review the existing relay/antenna selection algorithms and present our motivations of improving the existing schemes. Third, we propose three greedy relay/antenna selection algorithms, that is, doubly zero-forcing (ZF) greedy capacity maximization (DZF-GCM), greedy capacity maximization (GCM), and greedy mean square error (MSE) minimization (GMM) algorithms, to optimize the system based on various performance metrics. The effectiveness of the proposed schemes is corroborated by our simulation results followed by comprehensive discussions on the performance comparison of various algorithms to provide more insights on this topic.

This paper considers the precoder design issue of bidirectional networks in which each node is equipped with multi-antenna. In contrast to the conventional research of two way relay network, this paper adopts a more general scenario, a multi-relay multi-user network is considered. Firstly, assuming perfect channel state information is available, this paper investigates the precoding design for the relays and users with aim of minimizing the sum minimum square error. Then, this paper takes a more practical hypothesis into account by analyzing the channel estimation error. Utilizing the alternative optimization method, the main problem is divided into three decoupled subproblems and solved respectively. It is shown that in both cases, the proposed precoding algorithms outperform the existing schemes.

This paper investigates the problem of joint design of relay precoders and receivers based on the minimum mean-square-error (MMSE) criterion in multi-hop bi-directional multiple-input multiple-output (MIMO) amplify-and-forward (AF) relay systems. In contrast to the conventional research on two-way relay systems, we combine a multi-hop relay system with a bi-directional relay system which further enhances the system performance. By decoupling the original highly non-convex problem into three sub-problems, we propose an iterative algorithm to alternatively optimize relay precoders and receivers. Numerical simulation results show that the proposed iterative algorithm outperforms other algorithms in terms of bit-error-rate (BER).

Vehicular Ad hoc Networks(VANETs) enable plenty of important applications for vehicles, such as accident prevention and traffic jam avoidance. However, VANETs can hardly provide reliable connectivity between vehicles, which makes data dissemination of the aforementioned applications extremely difficult. Compared with VANETs, 3GPP cellular networks(e.g., LTE), offer much more reliable connectivity. Furthermore, cellular networks ensures timely dissemination in large scales due to the broadcast nature. In this paper, we deploy a cellular-VANET heterogenous network achitecture to realize efficient data dissemination. In the heterogenous networks, a part of vehicles are selected as mobile gateways to connect the two kind of networks. Later, we apply the coalition game theory to stimulate vehicles to join coalitions which can maximize the efficient data rate. The simulation results show that, by following the protocal, maximin overall effective data rate can be achieved.

Mobile and wireless communication has been evolved from the basic model for providing point-to-point (PtP) voice centric services into more complicated service provision technologies with point-to- multipoint (PtM) transmission mode, such as MBMS in 3GPP and BCMCS in 3GPP2. On the other hand, the evolution of mobile and wireless communication has also resulted in a large number of wireless technologies such as UMTS cellular network, WiMAX and WLAN. As a result, issues related to multicast/broadcast service over heterogeneous networks will be more complex, interesting and valuable. In this paper, we propose a solution aimed to provide seamless and ubiquitous support for multicast/broadcast service on heterogeneous accesses. Additionally, a vertical handover policy named PtM First for multicast resource management in heterogeneous networks is demonstrated.

This paper addresses the problem of joint design of user precoders and receivers as well as the relay precoder based on the minimum mean-square-error (MMSE) criterion in the multi-user amplify-and-forward (AF) two-way multiple-input multiple-output (MIMO) relay systems with analog network coding (ANC). By decoupling the original highly nonconvex problem into three sub-problems, we propose an iterative algorithm to repeatedly optimize precoders and receivers. The convergence of the algorithm is ensured since the updated solution is optimal to each sub-problem. In addition, a novel channel switching technique at the relay node is implemented as means of exploring different local optimal solutions to further improve the system performance. Numerical simulation results demonstrate that the proposed iterative algorithm outperforms other algorithms in terms of both bit error rate (BER) and mean square error (MSE).

We propose a novel Channel Quality Indicator (CQI) calculation scheme in LTE\LTE-A systems. SNR-CQI mapping scheme, as well as SINR-CQI mapping scheme, is extensively studied in previous works. However, these kinds of CQI mapping schemes always provide imprecise results in fading channels, since all of them ignore the channel quality degeneration caused by other factors. In this paper, we further improve CQI calculation by considering the impact of multipath delay spread. The calculation scheme is presented in details. In order to guarantee the converge of CQI calculation, a Block Error Ratio (BLER) based converge algorithm is proposed. Simulations show that our calculation scheme can select CQIs more precisely, and achieve better throughput performance than traditional schemes. Furthermore, our scheme converges much faster than previous schemes.

In this paper, we consider a dual-hop Multiple Input Multiple Output (MIMO) relay wireless network, in which a source-destination pair both equipped with multiple antennas communicates through a large number of half-duplex amplify-and-forward (AF) relay terminals. Two novel linear beamforming schemes based on the matched filter (MF) and regularized zero-forcing (RZF) precoding techniques are proposed for the MIMO relay system. We focus on the linear process at the relay nodes and design the new relay beamformers by utilizing the channel state information (CSI) of both backward channel and forward channel. The proposed beamforming designs are based on the QR decomposition (QRD) filter at the destination node which performs successive interference cancellation (SIC) to achieve the maximum spatial multiplexing gain. Simulation results demonstrate that the proposed beamformers that fulfil both the intranode array gain and distributed array gain outperform other relaying schemes under different system parameters in terms of the ergodic capacity., 18 pages, 6 figures

Recursive minimum mean-square-error estimation (MMSE) with low-complexity computation is considered for on-line implementation of channel acquisition in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. The channel correlation matrix is estimated by three approaches respectively, i.e., averaging measurements, direct tracking signal subspace of measurements and iterative calculation from measurements. Simulations demonstrate that the MMSE-based algorithms will obtain higher accuracy than least square estimation and its recursive pattern. In comparison of the three approaches, it is shown that the method of tracking signal subspace of measurements, which can separate the measurement space into signal subspace and its orthogonal noise subspace, is comparable to optimal MMSE estimation.

This paper presents a robust least square constant modulus algorithm (LSCMA) for interference cancellation based on subspace decomposition in CDMA system. The conventional least square constant modulus algorithm (LSCMA) is easy to capture the interference signals in the system that has several constant modulus signals. In order to overcome this shortage, a linearly constrained LSCMA algorithm is proposed by applying the linear constrained condition to the LSCMA, thus makes the algorithm converge to the desired user. To further enhance the performance, we apply the subspace decomposition to autocorrelation matrix of the received signal, and combine the Lagrange method and the partial Taylor-series expansion to update the weight vector. To reduce the computational complexity, an orthogonal projection approximation subspace- tracking (OPAST) algorithm is employed for adaptive signal subspace estimation. The simulation results demonstrate that the proposed algorithm has lower complexity, superior performance and is more robust in the case of random initial value. many constant modulus signals. Moreover, the LSCMA is also sensitive to the selection of the initial value (8), and the performance degrades significantly when the initial value is selected randomly. In this paper, a robust LSCMA based on subspace decomposition is proposed for interference cancellation. It uses the spreading code of the desired user to impose the linear constraint on the LSCMA, which can ensure that the algorithm converges to the desired user. The subspace decomposition is applied to the autocorrelation matrix of the received signal, which makes the algorithm update in the signal subspace. Thus the energy of the useful signal is increased, and thereby the corresponding detection performance is improved for any initial value. To obtain the weight vector, the Lagrange method and partial Taylor-series expansion are exploited to solve the optimal solution of the cost function. Moreover, an OPAST subspace tracking algorithm (9) is exploited for adaptive signal subspace estimation to reduce the computational complexity. It is shown that the proposed LSCMA can achieve better SINR performance than the conventional LSCMA with much less complexity, and is relatively more insensitive to the initial value.

Single carrier frequency division multiple access (SC- FDMA) has been adopted as a possible air interface for future wireless networks as it combines the advantages of Orthogonal Frequency Division Multiple Access (OFDMA) and the low envelope variation properties of single carrier (SC) transmission. The classical transmit antenna diversity technique as Space- Frequency Block Coding (SFBC) will harm single-carrier property and thus enhance the power amplifier efficiency of the mobile terminal. To solve this problem, a modified scheme of SFBC compatible with SC-FDMA is proposed in this paper. The proposed SFBC scheme is based on the groups rather than the symbols which remains the same signal distribution as the equivalent SC transmission. As a result, the PAPR of the proposed SFBC scheme is reduced. Simulation results show that the proposed SFBC scheme has good PAPR and Bit Block Error Rate (BLER) on frequency selective MIMO channels. Keywords-SC-FDMA;transmit diversity; SFBC; PAPR

This paper deals with the design and analysis of low complexity user scheduling algorithm in multiantenna broadcast (downlink) systems under zero-forcing multiplexing. By using quantization technology, the channel matrix can be divided into serval unoverlapped channel regions. Based on the quantized channel regions, we can get semi-orthogonal region sets. The presented user scheduling algorithm in this paper is based on using the semi-orthogonal region sets. Simulation results shows that this algorithm can achieve a sum rate close to the full searching algorithms while with much lower complexity than those of the previous algorithms.

This paper investigates the resource allocation problem in the downlink of OFDMA cooperative relaying networks with one source (base station) and multiple relay and destination nodes. Assuming that the base station knows all the instantaneous channel gains of all links, we propose a dynamic joint subchannel and power allocation (SPA) scheme whose objective is to maximize the worst user's data rate with the constraint of total transmission power. Since the optimal solution to this combinatorial problem is extremely computationally complex, we propose a low-complexity suboptimal algorithm that allocates subchannel and power separately. In the proposed algorithm, subchannels are firstly paired by relay nodes according to their equivalent channel gains and then assigned to a specific user. Subsequently, an optimal power distribution algorithm is designed for the proposed subchannel allocation (SA) scheme. The simulation results show that the performance of the proposed algorithm approaches asymptotically to that of the optimal one, and maximal fairness is guaranteed for all users.

In this paper, we consider the dynamic subchannel allocation problem in OFDMA-based selective relaying networks. Our goal is to maximize the total throughput under the constraint of total transmission power, while guaranteeing fairness on sub-channel occupation by multiple destination nodes (users). Since the optimal solution to this optimization problem is extremely computationally complex to obtain, we decompose the original optimization problem into two subproblems. Firstly, we assign subchannels to the users with the best equivalent channel gains for them under the assumption of equal power distribution among all subchannels. Secondly, water-filling method is adopted to distribute the power to the determined links. Simulation results show that the performance of the proposed algorithm approaches asymptotically to that of the optimal one, while reducing computational complexity from exponential to linear with the numbers of subchannels, relay nodes and users. It is also shown that subchannel permutation (SP) scheme brings additional throughput gain to DF cooperative transmission.

This paper deals with the design and analysis of low complexity user scheduling algorithm in multi-antenna broadcast (downlink) systems under zero-forcing multiplexing with limited feedback. By using quantization technology, the channel matrix can be divided into several unoverlapped channel regions. Based on the quantized channel regions, we can get semi-orthogonal region sets. Then the transmitter can carry out user scheduling by using the feedback channel direction information (CDI), channel quality information (CQI) and the quantized semi-orthogonal channel region sets. Simulation results show that the presented user scheduling algorithm can achieve a sum rate close to the full searching algorithms while with much lower complexity than those of the previous algorithms.

The decision-directed space-alternating generalized expectation-maximization (SAGE) algorithm is introduced in [1] to estimate the channel and track the channel varying for OFDM systems with transmitter diversity. However, this method is based upon a discrete Fourier transform (DFT), which will cause power leakage and result in an error floor in a multipath channel with non-sample-spaced time delays. In order to overcome this problem, a low rank approximation method is presented by using the signal subspace of the channel frequency autocorrelation matrix. Furthermore, a modified fast subspace tracking algorithm is introduced to adaptive estimate the signal subspace by using a space–time block coded training blocks sent at regular interval. Simulation results show the advantages of the proposed technique for MIMO-OFDM systems in time-varying non-sample-spaced wireless channels.

This paper focuses on subchannel and power allocation problem in OFDMA-based decode-and-forward (DF) cooperative relay networks. The objective of this problem is to maximize the total data rate under the constraints of joint total transmission power and subchannels occupation, while maintaining the maximum fairness among multiple relay nodes. We transform this mixed integer programming problem to a standard convex optimization one through Lagrangian relaxation method. Accordingly, the optimal solution can be achieved by using Karush-Kuhn-Tucker (KKT) conditions. In addition, we propose two suboptimal subchannel allocation schemes with and without subchannel permutation (SP), which reduce significantly the computational complexity with small performance loss. The simulation results show that the performance of the proposed suboptimal algorithms with SP approaches asymptotically that of the optimal algorithm and with the increment of the number of relay nodes.

This paper deals with design and performance analysis of transmit precoder optimization for MIMO-OFDM systems with limited feedback of channel state information (CSI). We assume that the receiver has perfect channel knowledge while the transmitter has only partial channel knowledge from limited feedback. We propose MSE-based optimal codebook design algorithm for MIMO-OFDM precoded spatial multiplexing systems under a specific average power constraint. The optimal precoder has the structure of a precoding and power allocation for each mode obtained by water-filling process. We derived the closed form solution for power allocation in the MSE- sense. Simulation results show that the MSE-based codebook construction algorithm with hybrid design of power allocation and precoding can achieve better performance than that of equal power allocattion based codebook in the previous works.

A cell identification scheme for OFDM cellular systems is proposed, which uses only one OFDM symbol with several identical slots as preamble. After performing OFDM timing/frequency synchronization, the UE identifies its cell ID by a novel scheme composed of cell group identification and cell index identification. Each cell group is distinguished from others by a unique subcarrier mask, which is an m-sequence. It activates or deactivates a subset of the subcarriers. Furthermore, cells with different indices in the same cell group load different differentially coded sequences on the adjacent active subcarriers. The UE recognizes the cell-group-specific mask via power detection of the received frequency domain signal. Then it identifies the cell index from differential demodulation and detection of the cell-index-specific sequence. Simulation results show that the proposed scheme is able to support a very large number of cell IDs and it works well even in bad multi-cell environment

Since accurate channel state information is essential to diversity combination, coherent detection and decoding in a wireless MIMO-OFDM system, this paper presents a channel estimation method using adaptive filters in wireless MIMO-OFDM systems. Though this method presupposes no prior knowledge of channel statistics, it can track or estimate time-varying channel parameters instantaneously with the help of pilot symbols and adaptive filters. Simulation results have proved this method using adaptive filters has better performance than another method based on a least-square (LS) algorithm. And the method using a least-mean-square (LMS) filter has lower computational complexity than that using a recursive-least-squares (RLS) filter. However, the channel estimation method using the RLS filter has better performance and faster convergence than that using the LMS filter. Therefore, we can select a fitter channel estimation method using different filters according to its characteristics

A fast frequency offset estimation scheme for OFDM is proposed. This scheme is low-overhead oriented, which uses only one OFDM symbol with L identical slots as preamble. By extracting the phase from correlation between two identical halves of the preamble, the fractional frequency offset is estimated and then compensated. After reshaping the compensated preamble into many L-point sub-symbols, which are processed by FFT algorithm, the estimate of integer frequency offset is accomplished by finding the maximum magnitude of the combined frequency domain signals. To further reduce the computational load of the algorithm, the scheme is carried out in a multistage manner. Simulation results show that the proposed scheme exhibits good performance, while maintaining a low complexity

This paper proposed a new LMS based adaptive CCI cancellation algorithm for space-time block coded orthogonal frequency division multiplexing (STC OFDM) systems. We apply LMS based adaptive channel estimation by orthogonal pilot patterns to identify channel information of interference cells. And by the identical channel information of different cells, we can easily reconstruct the signal of received signal, and then subtract co-channel interference cancellation (CCI) signal from the received signal. Simulation result shows that the proposed approach can achieve enhancement of system performance

Considering that channel estimation is crucial for coherent detection, a blind channel estimation method based on linear precoding for orthogonal frequency-division multiplexing (OFDM) systems is proposed in this paper. The proposed linear frequency-domain precoder is applied to each pair of blocks before they enter the OFDM system. Due to the introduced structure of precoder, the frequency-selective channel can be identified at the receiver based on cross-correlation operations, singular value decomposition (SVD) and resolving the scalar ambiguity. Because the linear frequency-domain precoder is creatively employed to channel estimation, the proposed blind method is computationally simple and requires no prior statistical information of channel or noise. And the proposed blind method has high spectral efficiency because it exploits no training sequence. Computer simulations have proved that this proposed blind method can identify the frequency-selective channels perfectly and have a good performance

MIMO-OFDM systems are considered as the solution scheme for future wideband wireless communication systems. And channel state information play a crucial role in data detection module. But Kalman filtering (KF) is a linear processing method which is not fit for processing nonlinear problem. While wireless channels have some nonlinear characteristics. Owing to the above reasons, this paper describes a channel estimation method based on extend Kalman filtering (EKF) for MIMO-OFDM systems. The proposed method based on EKF can exploit pilot symbols and an extended Kalman filter to implement channel estimation without the aid of any prior knowledge of channel statistics. In comparison with the channel estimation methods based on the least square (LS) and the least mean square (LMS) algorithms, the method base on EKF has better performances theoretically. Computer simulations also demonstrate the channel estimation method based on EKF outperforms the channel estimation methods based on LS and the LMS. Hence, the channel estimation method based on EKF can offer a dramatic system performance improvement at the cost of modest computational complexity

In this paper, a novel preamble which is composed of two OFDM training symbols with different numbers of identical parts is designed for OFDM systems. Based on the designed preamble, we propose a high performance frequency offset estimator by jointly using the CFO estimations independently obtained from the two training symbols. By elaborately selecting the values of the numbers of identical parts, the proposed estimator can estimate frequency offset over tens of the subcarrier spacing while achieving a superior estimate performance.

The frequency offset estimation for OFDM systems using the correlations of several identical parts in the preamble is addressed. We design a novel preamble which is composed of one irregular OFDM training symbol block with odd numbers of identical parts and one regular OFDM training symbol block with even numbers of identical parts. Based on the designed preamble, we propose a novel frequency offset estimator. Simulation results show that the proposed frequency offset estimator has the larger estimate range advantage over the conventional estimator while maintaining approximately the same performance.

Since accurate channel state information is crucial for coherent detection in a wireless MIMO-OFDM system, the performance of the MIMO-OFDM system critically depends on the availability of accurate channel estimation. This paper presents a channel estimation method base on particle filtering for wireless MIMO-OFDM systems. Based on the concept of sequential importance sampling and the use of Bayesian theory, particle filtering is particularly useful in dealing with nonlinear and non-Gaussian problems such as wireless channel estimation. Although this method presupposes no prior knowledge of channel statistics, it can track time-varying channel parameters instantaneously with the help of pilot symbols and particle filters. Computer simulations confirm that this method base on particle filtering has better performance than the other methods which are based on extended Kalman filtering (EKF) and LMS filtering.