This paper investigates the tightness of existing bounds on the quadratic Gaussian distortion-rate-perception functions with limited common randomness and the i.i.d. output constraint, under perception measures based on the Kullback–Leibler divergence and the squared Wasserstein-2 distance. For the squared Wasserstein-2 distance-based perception measure, we improve the best-known lower bound by introducing a tunable parameter. Moreover, via the connection between rate-distortion-perception coding and entropy-constrained scalar quantization, it is revealed that all existing bounds, including the improved one, are generally not tight in the weak perception constraint regime. Our findings shed light on the information-theoretic performance limits of rate-distortion-perception coding and offer guidelines for developing practical schemes.

In recent years, in-band full duplex (IBFD) has garnered significant attention in wireless communications due to its potential to enhance spectral efficiency. To fully exploit the benefits of IBFD, we design a novel medium access control (MAC) protocol for wireless local area networks (WLANs), which takes into account the realities of asymmetric traffic. However, key challenges involve inter-station interference within asymmetric topologies and wastage of idle time slots under asymmetric traffic conditions. We propose a successive full-duplex communication (SFD) protocol, integrating a CSMA/CA-based uplink selection mechanism and a weight-based downlink selection algorithm to minimize interference probabilities. Furthermore, SFD incorporates a control frame structure, power control algorithm, and successive interference cancellation (SuIC) technique to address the challenge of control frame interference in continuous IBFD communication. Both theoretical analysis and experimental evaluations demonstrate that SFD achieves a 52% increase in throughput compared to the 802.11 Distributed Coordination Function (DCF) with Request to Send/Clear to Send (RTS/CTS) and a 25% improvement over A-Duplex.

Dense deployment of small base stations (SBSs) within the coverage of macro base station (MBS) has been spotlighted as a promising solution to conserve grid energy in hybrid-energy heterogeneous cellular networks (HCNs), which caters to the rapidly increasing demand of mobile user (MU). However, MUs in the ultradense cellular network experience handover events more frequently than in conventional networks, which results in increased service interruption time and performance degradation due to blockages. In addition, blindly increasing the number of SBSs not only results in an increased cost for network operators but also brings serious system energy consumption and interference. In this article, we propose a joint user association and SBSs configuration scheme for maximizing energy efficiency (EE) in hybrid-energy HCNs. Specially, an association model with dual connectivity for MUs where they are connected simultaneously with SBSs and MBSs is first proposed to reduce frequent handover, which is also presented to preferentially select SBSs that can provide data transmission for MUs under the user association constraints according to the maximum system EE. And then the ratio between the number of SBSs and the number of MUs for SBSs configuration is analyzed to reduce interference and energy consumption under the tidal effect of HCNs. Furthermore, the EE utility function of joint user association and SBSs configuration is extended, and the Dinkelbach and Lagrangian algorithms are jointly optimized to solve the EE utility function. Finally, numerical simulation results are provided to demonstrate the feasibility of the proposed scheme. It is shown that the proposed scheme outperforms other schemes and can also maximize the EE in hybrid-energy HCNs.

We consider broadcasting a block of data packets to multiple users via instantly decodable network coding (IDNC) under the semi-online feedback transmission mode. In this paper, we first introduce a new class of IDNC schemes called lightweight IDNC, tailored for wireless broadcast with stringent computational load at the receiver end. Unlike traditional IDNC that may encode a larger number of original packets together, lightweight IDNC limits each coded packet to a combination of at most two original packets. Explicit lower bounds of the total completion delay as well as the decoding delay are respectively obtained for arbitrary lightweight IDNC schemes. We further investigate the number of transmission rounds as another performance metric, and explicitly characterize its distribution and expectation. The characterizations apply to arbitrary partition-based IDNC schemes, including the lightweight IDNC schemes considered in this paper. A new efficient algorithm is also proposed to construct lightweight IDNC schemes which grants the original packets with lower coding opportunity a higher priority to be encoded. Numerical analyses demonstrate that the lightweight IDNC schemes constructed by the new algorithm not only achieve lower completion and decoding delays in comparison with the ones constructed by the existing algorithm but also adhere closely to theoretical lower bounds, demonstrating their efficiency and practical utility.

The distortion-rate function of output-constrained lossy source coding with limited common randomness is analyzed for the special case of the squared error distortion measure. An explicit expression is obtained when both the source and reconstruction distributions are Gaussian. This further leads to a partial characterization of the information-theoretic limit of quadratic Gaussian rate-distortion-perception coding, with the perception measure given by either the Kullback-Leibler divergence or the squared quadratic Wasserstein distance, from which Wagner’s result for the perfect realism setting and Zhang et al.’s result for the unlimited common randomness setting can be recovered as special cases.

Full-Duplex (FD) has been widely recognized as one of the core technologies to enhance the spectral efficiency (SE) in the fifth generation (5G) cellular networks. FD technology (compared to traditional Half-Duplex (HD) technology in theory) can achieve twice the SE of cellular networks, but it introduces severe self-interference (SI) and co-channel-interference (CCI). Multi-domain (antenna-, radio frequency- and digital-domain) SI cancellation (SIC) techniques are proposed to reduce SI to a level close to the noise floor. However, due to the severe impact of Doppler shift and the absence of prior information, eliminating CCI is more challenging than eliminating SI, which has become a prominent obstacle to improving the performance of FD cellular networks. To achieve high-performance CCI cancellation (CCIC), perfect channel state information (CSI) is required. In this paper, we propose a superimposed pilot (SP) scheme for CCIC in FD cellular networks. Moreover, to address the Doppler shifts in FD cellular networks, two new SP-based channel estimation algorithms are developed for CCI channel and uplink/downlink channel, respectively. Furthermore, the Cram´er-Rao Lower Bounds (CRLBs) are also theoretically derived. In addition, we derive maximum achievable sum rate with imperfect CCIC in FD cellular networks. Finally, numerical results show that our proposed SP scheme outperforms the conventional time-multiplexed pilot (TP) scheme in terms of CCIC performance, BER performance and maximum achievable sum rate.

In the study of packet-level random linear network coding (RLNC) in wireless broadcast, RLNC over$\mathbf{GF}(2^{L})$is known to asymptotically achieve the optimal completion delay with increasing$L$. Utilization of guessing random additive noise decoding (GRAND) at physical layer can help leverage RLNC packets to generate syndromes so as to reduce packet erasure probabilities and thus further improve the completion delay performance. Prior to this work, only few studies investigated GRAND-assisted RLNC and they restricted to GF(2)-coding. In this paper, we first provide a general framework to formulate the decoding process of GRAND-assisted RLNC over$\mathbf{GF}(2^{L})$for$L\geq 1$. Even for GRAND-assisted GF(2)-RLNC, the formulation is more complete than previous considerations in the sense that it takes the a priori information of which packets have errors into consideration. In addition, we propose a novel GRAND-assisted$\mathbf{GF}(2^{L})$-RLNC scheme whose computational overhead introduced by GRAND is negligible. We theoretically derive lower bounds on the distribution as well as an upper bound on the expected value of the completion delay of the proposed scheme. Numerical results also demonstrate a reduction in average completion delay for the proposed new GF(28)-RLNC scheme, when compared to existing approaches.

This study investigates the actual impact of ChatGPT on human resource management (HRM) occupations and compares it with assessments from large language models (LLMs). Using data from the Occupational Information Network (O*NET), we developed a novel methodology combining real-world evidence from Google search results with evaluations from GPT-4, GPT-3.5, and Claude 3 Opus. Our findings reveal significant variations in the degree of exposure among HRM occupations. Training and Development Managers were the most exposed, with 86.52% of their tasks potentially automated by ChatGPT, while Labor Relations Specialists were the least exposed at 11.08%. Notably, LLM assessments consistently overestimated the exposure levels by an average of 30% compared to real-world evidence. This discrepancy highlights the importance of critically evaluating LLM capabilities in task automation. Our research contributes to understanding AI's impact on HRM practices and provides valuable insights for professionals adapting to the AI era. It also underscores the need for caution when relying solely on LLM assessments for workforce planning and development.

Active intrusion detection on network traffic streams becomes a crucial research problem, since it tries to maximize the effectiveness with limited labeled instances. The closely distributed anomalies of different categories and dynamic network traffic stream make it still quite a challenging issue. Therefore, we propose a Lightweight, Adaptive and Perspicacious Active Intrusion Detection method on network traffic streams, called LAPAID. We design novel lightweight anomaly detection clusters with density-aware hash cells, which successfully capture evolving data distribution. The anomaly detection clusters are incrementally updated in an approximate manner, and aggregated with a straightforward but effective metric divergences. At last, LAPAID detects anomalies and queries the instances for manual labels by measuring the density in hash cells of each cluster, effectively distinguishing closely distributed anomaly classes. Comprehensive experiments on several real-world data sets show that LAPAID outperforms previous methods, improving F1scores by 16.17% on average.

We consider broadcasting a block of data packets to multiple users via instantly decodable network coding (IDNC) under the semi-online feedback transmission mode. In this paper, we first introduce a new class of IDNC schemes called lightweight IDNC, tailored for wireless broadcast with stringent computational load at the receiver end. Unlike traditional IDNC that may encode a larger number of original packets together, lightweight IDNC limits each coded packet to a combination of at most two original packets. We obtain lower bounds on the total completion delay that apply to arbitrary lightweight IDNC schemes. We further investigate the number of transmission rounds as another performance metric, and explicitly characterize its distribution and expectation. The characterizations apply to arbitrary partition-based IDNC schemes, including the lightweight IDNC schemes considered in this paper. A new efficient algorithm is also proposed to construct lightweight IDNC schemes which grants the original packets with lower coding opportunity a higher priority to be encoded. Numerical analyses demonstrate that the lightweight IDNC schemes constructed by the new algorithm not only achieve lower completion and decoding delays in comparison with the ones constructed by the existing algorithm but also adhere closely to theoretical lower bounds, demonstrating their efficiency and practical utility.

As a novel paradigm, Vehicular Edge Computing (VEC) can effectively support computation-intensive or delay-sensitive applications in the Internet of Vehicles era. Computation offloading and resource management strategies are key technologies that directly determine the system cost in VEC networks. However, due to vehicle mobility and stochastic arrival computation tasks, designing an optimal offloading and resource allocation policy is extremely challenging. To solve this issue, a deep reinforcement learning-based intelligent offloading and power allocation scheme is proposed for minimizing the total delay cost and energy consumption in dynamic heterogeneous VEC networks. Specifically, we first construct an end-edge-cloud offloading model in a bidirectional road scenario, taking into account stochastic task arrival, time-varying channel conditions, and vehicle mobility. With the objective of minimizing the long-term total cost composed of the energy consumption and task delay, the Markov Decision Process (MDP) can be employed to solve such optimization problems. Moreover, considering the high-dimensional continuity of the action space and the dynamics of task generation, we propose a deep deterministic policy gradient-based adaptive computation offloading and power allocation (DDPG-ACOPA) algorithm to solve the formulated MDP problem. Extensive simulation results demonstrate that the proposed DDPG-ACOPA algorithm performs better in the dynamic heterogeneous VEC environment, significantly outperforming the other four baseline schemes.

Person–job fit, which aims to predict the matching degree between a resume and a job, has become an effective way to overcome information overload in the recruitment market. Existing studies on person–job fit usually focus on the representation learning of textual data in jobs and resumes. Person–job fit is a highly nonlinear complex problem that is affected by several fields of features. We assume that it would bring benefits to comprehensively consider the numerical features, categorical features, and textual features of resumes and jobs. To this end, we propose a novel model based on the self-attention mechanism, named MUlti-Field Features representation and INteraction (MUFFIN) learning for person–job fit. The key idea is to explore meaningful feature representations and interactions. Specifically, we group all the features of resumes and jobs into several fields. And a module is introduced to learn the hidden vectors of feature correlations in each feature field. Along this line, we propose a module with the multi-head self-attention mechanism and a residual connection to further model the feature field interactions. Moreover, we utilize a multi-layer perceptron (MLP) to measure the matching score between a resume and a job. Finally, the experimental results on a real-world dataset validate the effectiveness of MUFFIN for person–job fit.

In this paper, multi-UAVs serve as mobile aerial ISAC platforms to sense and communicate with on-ground target users. To optimize the communication and sensing performance, we formulate a joint user association, UAV trajectory planning and power allocation problem to maximize the minimum weighted spectral efficiency among UAVs. This paper exploits the centralized and the decentralized deep reinforcement learning (DRL) solutions to solve the sequential decision-making problem. On one hand, we first introduce the centralized soft actor-critic (SAC) algorithm. Then, we explore the equivalent transformation of the optimization objective based on symmetric group, propose the random and the adaptive data augmentation schemes to design the replay memory buffer of SAC, and accordingly propose SAC algorithms assisted by data augmentation to tackle the transformed problem. On the other hand, the multi-agent soft actor-critic (MASAC), a decentralized solution, is also introduced to solve this sequential decision-making problem. The experiment results reveal the effectiveness of the centralized and the decentralized solutions in considered scenarios. Specifically, the SAC assisted by the adaptive scheme significantly outperforms other centralized solutions in the training speed and the weighted spectral efficiency. Meanwhile, the decentralized MASAC algorithm behaves best in the early training speed.

In this article, we investigate the training optimization for multiple-input–multiple-output (MIMO)-aided Internet of Things (IoTs) systems that employ subarray-based intelligent reflecting surface (IRS). In order to overcome the nonlinear relationship between two cascaded channel matrices, the IRS can be divided into a series of subarrays, for which only an equivalent cascaded channel matrix should be estimated in each subarray. Correspondingly, the training sequence should be divided into multiple segments. By sufficiently utilizing the available statistical channel state information (CSI), either mean-square error (MSE) minimization or mutual information (MUI) maximization can be taken as the performance metric for optimizing the training sequence. A variety of fairnesses among different subarray channel estimations has been taken into account. Furthermore, in order to reduce the hardware cost of the power amplifier, we propose a two-stage training sequence structure, including a fully digital filter and a constant modulus sequence. To further reduce computational complexity, various low-complexity water-filling solutions are proposed. Numerical results demonstrate the accuracy and efficiency of the proposed solutions.

The machine-type communication (MTC) enables a broad range of applications from mission-critical services to massive deployment of autonomous devices in the Internet of Things (IoT) networks. To release more spectrum resources for facilitating the explosive traffic of MTC in ultradense Cellular-IoT (CIoT) networks, full-duplex (FD) technology has been considered as a candidate mechanic due to its respective advantages in terms of the spectral efficiency (SE). Compared with the traditional half-duplex (HD) technology, the FD technology can (in theory) attain twice the SE gain. Nevertheless, the performance of FD technology is severely limited by both the self-interference (SI) and the mutual interference (MI) in the presence of multiple users. What is more serious is that when FD technology is used in a multiuser communication system, the system performance is very sensitive to the service load of the entire network, and it may even appear fragile in an ultrahigh load environment. In this article, we will delve into investigating the performance of the FD technique in the CIoT networks by considering the impacts of a variety of aspects, including the SI cancelation capability (SICC) of the FD-mode devices, the network’s workload, as well as the devices’ distribution density (DDD), the purpose of which is to maximize both the SE and the sum throughput (ST) of the network by optimizing those critical parameters. It is shown that the FD mode is capable of improving the ST of the CIoT networks in either the low-traffic-volume or low-device-density regime, provided that the devices’ SICC could be up to 100dB. At the same time, research results show that further increasing both the devices’ density and the traffic load, even without compromising the FD devices’ SICC, will still help improve the performance superiority of FD technology. Numerical results show that by implementing an appropriate workload-driven mode-selection scheme, we can sufficiently exploit the FD/HD gain according to the instantaneous radio frequency environment.

As the next-generation wireless networks thrive, full-duplex and relay techniques are combined to improve the network performance. Random linear network coding (RLNC) is another popular technique to enhance the efficiency and reliability of wireless communications. In this paper, in order to explore the potential of RLNC in full-duplex relay networks, we investigate two fundamental perfect RLNC schemes and theoretically analyze their completion delay performance. The first scheme is a straightforward application of conventional perfect RLNC studied in wireless broadcast, so it involves no additional process at the relay. Its performance serves as an upper bound for all perfect RLNC schemes. The other scheme allows sufficiently large buffer and unconstrained linear coding at the relay. It attains the optimal performance and serves as a lower bound for all RLNC schemes. For both schemes, closed-form formulae to characterize the expected completion delay at a single receiver as well as for the whole system are derived. Numerical results are also demonstrated to validate the theoretical characterizations, and compare the two fundamental schemes with the existing one.

As the next-generation wireless networks thrive, full-duplex and relaying techniques are combined to improve the network performance. Random linear network coding (RLNC) is another popular technique to enhance the efficiency and reliability in wireless communications. In this paper, in order to explore the potential of RLNC in full-duplex relay networks, we investigate two fundamental perfect RLNC schemes and theoretically analyze their completion delay performance. The first scheme is a straightforward application of conventional perfect RLNC studied in wireless broadcast, so it involves no additional process at the relay. Its performance serves as an upper bound among all perfect RLNC schemes. The other scheme allows sufficiently large buffer and unconstrained linear coding at the relay. It attains the optimal performance and serves as a lower bound among all perfect RLNC schemes. Closed-form formulae for the expected completion delay of both schemes are derived. Numerical results are also demonstrated to verify the theoretical characterization and compare the two new schemes with the existing one.

The cellular vehicle-to-everything (C-V2X) networks support diverse kinds of services, such as traffic management, road safety, and sharing data. However, the safety issues cannot be ignored in the process of information transmission. In this article, a joint clustering and blockchain scheme is proposed for real-time information security transmission to prevent some vehicles from sending malicious messages to disrupt the traffic order at the crossroads in C-V2X networks. In this scheme, the dynamic stability of the cluster is maintained by updating the trust value of the vehicle nodes, which can improve the real time and accuracy of the information transmission. The modified Webster algorithm is presented to divert the traffic flow so as to reduce the traffic jams at the crossroads. Meanwhile, the blockchain technology is utilized to establish a vehicle trust management mechanism in C-V2X, which can avoid malicious tampering of vehicle information during information sharing and ensure the safety of vehicle information communication. The simulation results of the Veins simulation platform are provided to demonstrate the effectiveness of the proposed algorithm and verify that the proposed scheme can guarantee the security of real-time information transmission.

In wireless broadcast, random linear network coding (RLNC) over GF(2L) is known to asymptotically achieve the optimal completion delay with increasing L. However, the high decoding complexity hinders the potential applicability of RLNC schemes over large GF(2L). In this paper, a comprehensive analysis of completion delay and decoding complexity is conducted for field-based systematic RLNC schemes in wireless broadcast. In particular, we prove that the RLNC scheme over GF(2) can also asymptotically approach the optimal completion delay per packet when the packet number goes to infinity. Moreover, we introduce a new method, based on circular-shift operations, to design RLNC schemes which avoid multiplications over large GF(2L). The new RLNC schemes turn out to have a much better trade-off between completion delay and decoding complexity. In particular, numerical results demonstrate that the proposed schemes can attain average completion delay just within 5% higher than the optimal one, while the decoding complexity is only about 3 times the one of the RLNC scheme over GF(2).

In wireless broadcast, random linear network coding (RLNC) over GF(2L) is known to asymptotically achieve the optimal completion delay with increasing L. However, the high decoding complexity hinders the potential applicability of RLNC schemes over large GF(2L). In this paper, a comprehensive analysis of completion delay and decoding complexity is conducted for field-based systematic RLNC schemes in wireless broadcast. In particular, we prove that the RLNC scheme over GF(2) can also asymptotically approach the optimal completion delay per packet when the packet number goes to infinity. Moreover, we introduce a new method, based on circular-shift operations, to design RLNC schemes which avoid multiplications over large GF(2L). Based on both theoretical and numerical analyses, the new RLNC schemes turn out to have a much better trade-off between completion delay and decoding complexity. In particular, numerical results demonstrate that the proposed schemes can attain average completion delay just within 5% higher than the optimal one, while the decoding complexity is only about 3 times the one of the RLNC scheme over GF(2).

The technology of static user-centric virtual cell (VC) has been designed in the fifth-generation (5G) ultra-dense networks (UDNs) for alleviating both frequent handover and inter-cell interference. However, to provide the user-centric services, the fairness of resource management must be involved when the common vehicular-to-X (V2X) messages are multicast to the vehicle groups. In this paper, a dynamic user-centric virtual cell (DUVC) scheme is proposed for updating adaptively the VC through the mobile tracking of the vehicles. Furthermore, an approximation algorithm is proposed for solving the max-min-fair problem of resource management in V2X communication in order to better support V2X services throughout the service VC. Numerical results are provided for demonstrating that the proposed DUVC scheme is suitable for implementing in the V2X communication. Finally, the proposed algorithm is shown to outperform three other existing algorithms in terms of fairness of resource management.

In this work, we investigate in depth the two timescale robust system energy efficiency (EE) precoding design for the multiuser dual-polarized multiple-input multiple-output (MIMO) system. To achieve good performance, low feedback overhead as well as low implementation complexity, the dual-structured linear precoding scheme is adopted, which is based on the two timescale channel state information (CSI) and the dual-polarized antenna structure. The subgrouping technique, which is based on polarization, is also utilized to divide spatially grouped users into co-polarized subgroups to further reduce channel feedback overhead. The proposed robust system EE precoding design can achieve the maximization of the worst-case system EE, with the norm-bounded channel errors of all users. This robust EE optimization is naturally decomposed into two parts. In the first part, based on the polarized spatial correlation information, the block diagonalization is utilized to design the preprocessing matrix. In the second part, based on the relationship between the mean square error and the signal-to-interference-plus-noise ratio, the linear precoding matrix can be optimized by utilizing the sign-definiteness lemma and the fractional programming technique. Specifically, the corresponding nonconvex EE fractional optimization problem is converted to a series of semidefinite programming problems, which are solved by the convex optimization method efficiently. Simulation results indicate that the proposed two timescale based dual-structured precoding has many advantages on the robust system EE performance in the dual-polarized multiuser MIMO system.

The task planning of satellite-ground time synchronization (SGTSTP) in global navigation satellite system is a complex many-objective ground station scheduling problem. In this paper, we first provide a mathematical formulation of the over-subscribed problem and compare with traditional scheduling problems likes job-shop scheduling problem (JSP) and satellite range scheduling problems (SRSP). In application of the Beidou Navigation System of China, with the limit of ground resource and visible time between satellites and antennas, it is no doubt a difficult problem to solve, besides, there are several objectives for SGTSTP. To solve this SGTSTP problem with efficiency and effectiveness, we propose a solving method based on decomposition-and-integration (DI), and transform SGTSTP from many-objective optimization problem (MaOPs) into a multi-objective optimization problem (MOP), to make it suitable for a multi-objective evolutionary algorithm (MOEA). Meanwhile, evolutionary many-objective optimization algorithm (EMOA) is used for original objectives as comparison. We embed the DI method into two classes of evolutionary algorithm frameworks. DI-MOEA works on a transformed two-objective version of the SGTSTP while DI-EMOA deals with the original four-objective SGTSTP problem. Computational results on two well-designed instances show that the DI-MOEA achieves worse convergence and diversity but better objective value and computational efficiency compared to the DI-EMOA.

The financial security is the lifeblood of a company. Effective identification of corporate financial fraud can protect the safety of funds for investors in some sense. This paper proposed a fraud identification model about corporate financial fraud problem based on principal component analysis (PCA) and BP neural network (BP NN). Compared with other methods, there was a significant improvement in the recognition rate of fraud on financial statements. The experimental results shown that our model is effective, which can accurately identify financial fraud and guarantee the 's financial security.

The ACP theory plays an important role in modeling and controlling complex, uncertain systems. Parallel loading and unloading is the specific application of parallel theory in the field of parcel handling. This paper proposes the basic framework of the parallel loading and unloading system. Under this framework, the physical loading and unloading process is described by constructing a artificial loading and unloading system. On this basis, the artificial system predicts the best loading and unloading solution through computational experiments. The physical loading and unloading system executes the solution from the artificial system. Finally, the parallel execution builds a bridge between the physical system and the artificial system. The parallel system will be updated and optimized continuously. Parallel loading and unloading is one smart technology toward intelligent logistics, which provides a new methodology for parcel handling technology.

Both clustering and cluster-head vehicles (CHVs) cooperative communication have been employed for reducing traffic congestion to improve road traffic efficiency in cooperative vehicular networks. In this paper, an iterative optimization k-means clustering algorithm with lower complexity than previous algorithms is proposed. It can automatically generate multiple clusters according to the number of vehicles and quickly find the CHVs by avoiding delays caused by complex calculations. Moreover, a new optimization power allocation strategy with bidirectional incremental hybrid decode-amplify-forward protocol focusing on reducing the total power consumption of CHVs is proposed. This strategy can set the signal to noise ratio threshold as the critical point for selecting dynamically the bidirectional incremental amplify-and-forward or decoding and forwarding protocol with a lower outage probability to transmit information. Thus, the proposed power allocation strategy is capable of minimizing the total transmission power while ensuring a lower outage probability than previous approaches. Finally, the numerical results are provided for corroborating the theoretical results and demonstrate the efficiency of the proposed approaches. Note that through the numerical simulations we can find the critical point of the outage probability for the aforementioned protocols under different relay locations. This assists vehicles to select “relays” with the optimal cooperative position for vehicular cooperative communication system.

The device-to-device (D2D) communications mode has been regarded as an effective technique for solving/relieving the contradiction between the exponentially increased data traffic requirements of mobile customers and the essence of scarcity of radio resources in wireless communication networks. In the presence of unfavorable direct communication links between D2D peers, cooperative relays may play an important role in enhancing both reliability and flexibility of D2D communications. Aiming at maximizing the sum throughout of the network with a low computation complexity, a new scheme, which jointly considers a number of critical aspects, such as power control, interference limit based on the location information, optimal relay selection based on delineated area, and optimal link selection based range division, etc., is proposed in this paper. Numerical results reveal that the proposed scheme is capable of substantially improving the system's performance compared with either the existing brute-force technique or the area-division scheme. Furthermore, the proposed scheme also exhibits its advantages over the existing techniques in terms of computational complexity.

This paper provides symbol-error-rate (SER) performance analysis and minimum power allocation for multi-source multi-destination cooperative vehicular networks using the hybrid decode-amplify-forward (HDAF) cooperative relaying protocol. Previous studies of power allocation minimize the outage probability subject to a total power constraint. Our approach aims to minimize the power allocation in order to maintain the SER below a specific threshold and thus it achieves lower power consumption. Numerical tests show that HDAF has significantly reduced SER compared with the forward strategies of amplify-and-forward (AF) and decode-and-forward (DF). Furthermore, the power consumption in our proposed approach is much less than that in AF and DF.

In this paper, we investigate the problem of recovering positive semi-definite (PSD) matrix from 1-bit sensing. The measurement matrix is rank-1 and constructed by the outer product of a pair of vectors, whose entries are independent and identically distributed (i.i.d.) Gaussian variables. The recovery problem is solved in closed form through a convex programming. Our analysis reveals that the solution is biased in general. However, in case of error-free measurement, we find that for rank-r PSD matrix with bounded condition number, the bias decreases with an order of O(1/r). Therefore, an approximate recovery is still possible. Numerical experiments are conducted to verify our analysis.

The device-to-device (D2D) communication has become one of the most promising methods for alleviating the deficiency of wireless spectrum. In spite of the potential gains brought by activating D2D communications, the problem of severe interference between cellular and D2D users cannot be ignored. In this paper, we introduce the power-control scheme based on interference limited area (ILA) for alleviating the abovementioned interference. In a single cell where there are M cellular user equipments (CUEs) supporting both the conventional cellular mode and the D2D mode, the controlling thresholds λD and λC are defined for the D2D transmitter (DT) and the base station (BS), respectively; we forbid all the DT from transmission within ILA-S1 but activating DT only within the inner section of ILA-S2, where ILA-S1 and ILA-S2 are defined as the areas in which the signal-to- interference ratio (SIR) is higher than λC and λD, respectively. Furthermore, we propose a novel resource-allocation scheme relying on interference control mechanism based on the criteria of "maximum/minimum power of DT". Numerical results show that the proposed scheme is capable of achieving the best system performance in terms of capacity, where the optimal ILA size is attainable.

The family of conventional half-duplex (HD) wireless systems relied on transmitting and receiving in different time slots or frequency subbands. Hence, the wireless research community aspires to conceive full-duplex (FD) operation for supporting concurrent transmission and reception in a single time/frequency channel, which would improve the attainable spectral efficiency by a factor of two. The main challenge encountered in implementing an FD wireless device is the large power difference between the self-interference (SI) imposed by the device’s own transmissions and the signal of interest received from a remote source. In this survey, we present a comprehensive list of the potential FD techniques and highlight their pros and cons. We classify the SI cancellation techniques into three categories, namely passive suppression, analog cancellation and digital cancellation, with the advantages and disadvantages of each technique compared. Specifically, we analyze the main impairments (e.g., phase noise, power amplifier nonlinearity, as well as in-phase and quadrature-phase (I/Q) imbalance, etc.) that degrading the SI cancellation. We then discuss the FD-based media access control (MAC)-layer protocol design for the sake of addressing some of the critical issues, such as the problem of hidden terminals, the resultant end-to-end delay and the high packet loss ratio (PLR) due to network congestion. After elaborating on a variety of physical/MAC-layer techniques, we discuss potential solutions conceived for meeting the challenges imposed by the aforementioned techniques. Furthermore, we also discuss a range of critical issues related to the implementation, performance enhancement and optimization of FD systems, including important topics such as hybrid FD/HD scheme, optimal relay selection and optimal power allocation, etc. Finally, a variety of new directions and open problems associated with FD technology are pointed out. Our hope is that this treatise will stimulate future research efforts in the emerging field of FD communications.

We investigate the joint optimization of the group power allocation and prebeamformer for joint spatial division and multiplexing (JSDM) in massive MIMO downlink systems. In contrast with the approximated block diagonalization (ABD) prebeamformer which is derived by heuristic method in the original JSDM scheme and is restricted to semi-unitary matrix, general prebeamforming matrix together with group power is optimized in the framework of per-user ergodic rate balancing. Thus, both flexibility and optimality are integrated in our work. To ease the difficulty in optimizing the exact ergodic rate, the deterministic approximation is employed. Based on the uplink-downlink duality approach, an iterative algorithm alternatively updating group power and prebeamformers is designed. It is shown that the optimization subproblems of the algorithm can be solved efficiently. Compared with the classic signal-to-noise-and-interference ratio (SINR) balancing algorithm for MISO downlink, the proposed algorithm has similar properties of both convergence and optimality. Numerical experiments are conducted to validate the effectiveness of the proposed algorithm.

A joint optimization method considering both Partial-Spectrum-Reuse (PSR) scheme and base-station-sleep (BSS) is proposed for improving the energy efficiency in heterogeneous networks (HetNets). We derive the coverage probabilities for both the macro-tier and micro-tier networks, followed by maximizing the HetNet's coverage probability through optimizing both the PSR factor and macro-micro base station's active probability ratio (APR). Furthermore, the problem of energy-consumption-minimization in the whole HetNet can be addressed by analyzing the relationship between the optimal PSR factor and APR. Numerical results show that the proposed joint optimization method is capable of saving network energy consumption of up to 50% when the signal-to-interference-and-noise ratio (SINR) target is set to be 20 dB.

The impact of both maximal ratio combining (MRC) and relay selection on the physical layer security in wireless communication systems is studied by analyzing some important factors, including the probability characteristic of the legitimate receiver (Bob) and malicious eavesdropper (Eve)'s end-to-end signal-to-noise ratio (SNR), the secrecy outage probability, and the average secrecy channel capacity over Rayleigh fading Channel. We assume that Bob receives its data from both the relay and the source by cooperative communication, provided that MRC is employed at the receiver. Compared to the conventional MRC methods, a higher spatial diversity order can be exploited by performing relay selection in the proposed method, as validated via both theoretical analysis and numerical simulation. The theoretical closed-form expressions for some figures of merit, e.g., the secrecy outage probability and the average secrecy capacity, are all consistent with the numerical results.

The main constraint to the performance improvement of two-tier heterogeneous network (HetNet) comes from the cross-tier interference (CTI) due to the frequency reuse among cells. A user-pairing aided uplink power control algorithm based on the non- cooperative game theory can be employed in consideration of user diversity gain for alleviating the CTI. In order to maximize the overall performance, the macro-tier users with higher channel gains and the femto-tier users with lower channel gains are scheduled alternately to be "active" in one time slot but to be "opposite" in the next time slot in the proposed scheme. Numerical results show that the proposed scheme is capable of outperforming the traditional stochastic schedule based strategy by more than 30% improvement in terms of average macrocell capacity. Furthermore, an obvious performance gain in terms of the percentage of femtocells that beyond their signal- to-interference-and-noise ratio (SINR) target can also be achieved by executing the macro-tier link- qualityprotection strategy.

In this paper, we investigate space-time network coding (STNC) in cooperative multiple-input multiple-output networks, where U users communicate with a common destination D with the aid of R decode-and-forward relays. The transmit antenna selection with maximal-ratio combining (TAS/MRC) is adopted in user-destination and relay-destination links where a single transmit antenna that maximizes the instantaneous received signal-to-noise ratio is selected and fed back to transmitter by receiver and all the receive antennas are combined with MRC. In the presence of perfect feedback, we derive new exact and asymptotic closed-form expressions for the outage probability (OP) and the symbol error rate (SER) of STNC with TAS/MRC in independent but not necessarily identically distributed Rayleigh fading channels. We demonstrate that STNC with TAS/MRC guarantees full diversity order. To quantify the impact of delayed feedback, we further derive new exact and asymptotic OP and SER expressions in closed form. We prove that the delayed feedback degrades the full diversity order to (R + 1)ND, where ND is the antenna number of the destination D. Numerical and Monte Carlo simulation results are provided to demonstrate the accuracy of our theoretical analysis and evaluate the impact of network parameters on the performance of STNC with TAS/MRC.

The problem of robust relay beamforming for the multiple-antenna amplify-and-forward (AF) relay network in the presence of an eavesdropper is studied in the paper, with the partial eavesdropper's channel side information (ECSI) scenario being considered. In our work, the uncertainty of ECSI is modeled by using a bounded region, which imposes independent constraints on the channel gain and direction. We propose a new rank-2 relay beamformer with a special singular value decomposition (SVD) structure, whose optimal solution for the worst-case secrecy rate maximization problem can be derived via simple line searching. Furthermore, the asymptotic optimality of the proposed rank-2 beamformer is proved in the high-relay-power region under certain condition, with the performance of the proposed beamformer being verified by using numerical experiments.

The performance analysis of optimal relay decode-and-forward (DF) selection for both the full-duplex (FD) and half-duplex (HD) relaying modes is studied, with some important factors such as the distributions of the received signal-to-noise ratio (SNR), the outage probability and the average channel capacity, etc., being taken into account. Different from the conventional relay selection schemes, the trade-off between the FD and HD modes is studied, with the former suffering from the impact of residual self-interference while the latter consuming more channel resources than the former by allocating two orthogonal channels for transmission and reception. The optimal power allocation (OPA) subject to individual power constrains (IPC) and sum power constrains (SPC) are also analyzed in the proposed FD scheme. In particular, the exact closed-form expressions for outage probability of the proposed FD relay selection scheme over independent and identically distributed (i.i.d.) Rayleigh fading channels are derived in this paper, with the validity of the proposed analysis being proven by simulation. It is also shown that the proposed FD scheme outperforms the HD mode in terms of average channel capacity by about 33.1%, provided that the self-interference can be successfully suppressed below the noise power level.

The design of a wireless sensor network is introduced for the metallurgical gas monitoring, in which the sensor node support a slot-based configurable gas sensor array both for metallurgical-specific and general purposes at the factory or far regions. The key technologies to compress the multisensor vector data is discussed with an amendatory LBG vector quantization and Huffman coding algorithms. Both the proposed network design and data compression schemes are verified with the hardware prototype and practical data. To the best of our knowledge, it is a novel exploration and practice for the applications of wireless sensor networks in the metallurgical industries, especially for the metallurgical gas monitoring.

The impact of an imperfect channel estimation on the amplify-and-forward (AF) mode cooperative communications systems is studied, with some important factors, including the probability characteristic of the secondary user's end-to-end signal-to-noise ratio (SNR), the outage probability, the symbol error probability (SEP) and the lower bound on the capacity, etc, being analyzed. As compared to the conventional relay selection schemes, less channel state information (CSI) feedback is required in the proposed method due to an outdated channel estimation being tolerable. The proposed scheme is validated by carrying out both theoretical analysis and numerical simulation, and the theoretical closed-form expressions for some figures of merit, including the outage probability, the SEP and the lower bound on the capacity, are consistent with the numerical results. The simulation results also prove that the performance of the proposed scheme is impacted considerably by some other critical parameters, including the number of relays, the channel correlation coefficient and the interference threshold. In the presence of multiple candidate relays, an optimum solution in terms of either outage probability or SEP performance can always be found within the SNR range of [0dB, 10dB].

The impact of outdated channel state information (CSI) on the capacity of amplify-and-forward (AF) partial relay selection systems is studied in this paper. The closed-form expressions for the distribution of received signal-to-noise ratio (SNR) in a multi-relay cooperative communications system is first derived, with independent and identically distributed (i.i.d.) Rayleigh fading channels being assumed in each wireless link. After that, the theoretical closed-form expressions for both outage probability and channel capacity of partial relay selection are derived, with four classical adaptive transmission techniques, including the constant power with optimal rate adaption (ORA), the optimal power and rate adaption (OPRA), the channel inversion with fixed rate (CIFR) and truncated channel inversion with fixed rate (TIFR), being considered. Numerical analysis proves that the channel capacity of partial relay selection is impacted considerably by some critical parameters, including the number of relays, the channel correlation coefficient and the end-to-end SNR, etc. It's also exhibited in the numerical results that among the four adaptive transmission techniques, the diversity order of OPRA is larger than that of TIFR, and the OPRA outperforms TIFR with about 0.15 bits/s/Hz in terms of average channel capacity.

In this paper, we present an analytical study of the bit error rate (BER) for interleaved single-carrier frequency-division multiple access (SC-FDMA) systems over independent but not necessarily identically distributed (i.n.i.d.) Nakagami-m fading channels with fading parameters {m} being integers when minimum mean-square error frequency-domain equalization (MMSE-FDE) is applied. Under the assumption of independent fading characteristics among channel frequency responses (CFRs) at the allocated subcarriers for a specific user, accurate numerical BER computation for square M-ary quadrature amplitude modulation (M-QAM) is developed by exploiting the statistics of the equalized noise. More importantly, the BER derivation is based on the real distribution of the CFRs without applying the widely used approximation of the CFRs in previous literature, resulting in a more accurate BER analysis. Monte-Carlo simulations are conducted to validate the analysis.

Frequency offset and channel estimation in cooperative orthogonal frequency division multiplexing (OFDM) systems is studied in this paper. We consider the scenario of two or more source nodes sharing the same relay, i.e., corelay cooperative communications, and a new preamble, which is central-symmetric in time-domain, is proposed to perform the frequency offset and channel estimation. The non-zero samples in the proposed preamble are sparsely distributed with two neighboring non-zero samples being separated by μ >; 1 zeros. As long as μ >; 2L - 1 is satisfied, the multipath interference can be effectively eliminated, where L stands for the channel order. Unlike [1], the proposed preamble has a much lower Peak-to-Average Power Ratio (PAPR). The interference among the multiple source nodes can also be eliminated by using a backoff modulation scheme on the proposed preamble in each source node, and the mean-square error (MSE) of the proposed Least-Square (LS) channel estimator can be minimized by ensuring the orthogonality among the source nodes. The Pairwise Error Probability (PEP) performance of the proposed system by considering both the frequency offset and channel estimation errors is also derived in this paper. For a given Signalto-Noise-Ratio (SNR), by keeping the total power consumption to the source nodes and the relay to be constant, the PEP can be minimized by adjusting the ratio between the power allocated to the source nodes and the total power.

Cell search as well as synchronization in the 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) system is performed in each User Equipment (UE) by using both the Primary Synchronization Signal (PSS) and Secondary Synchronization Signal (SSS), and the overall synchronization performance is dominated heavily by a robust PSS detection. Conventional non-coherent detector can achieve a reliable PSS detection based on the near-perfect auto-correlation and crosscorrelation properties of Zadoff-Chu (ZC) sequences [1], but at the cost of a relatively high computational complexity. This paper proposes two improved PSS detectors, i.e., Almost Half-Complexity (AHC) and Central Self-Correlation (CSC) detectors, by exploiting the central-symmetric property of ZC sequences. The AHC detector has exactly the same detection accuracy as that of the conventional detector but with 50% complexity being saved, and the proposed CSC detector can further reduce its complexity to 50% that of the AHC detector, however, at a cost of a slight accurate degradation. In order to mitigate the potential failure risk due to a large frequency offset in the proposed algorithms while at the same time keep the PSS detection accuracy un-degraded, an improvement of CSC, i.e., CSCIns, is also proposed. The performance of CSCIns detector is independent of the frequency offset, and numerical results show that the 90% PSS acquisition time of CSCIns is well within a 55ms duration with Signal-to-Noise Ratio (SNR) of -10 dB.

It has been well recognized that channel state information (CSI) feedback is of great importance for downlink transmissions of closed-loop wireless networks. However, the existing work typically researched the CSI feedback problem for each individual mobile station (MS), and thus, cannot efficiently model the interactions among self-interested mobile users in the network level. To this end, in this paper, we propose an alternative approach to investigate the CSI feedback-rate control problem in the analytical setting of a game theoretic framework, in which a multiple-antenna base station (BS) communicates with a number of co-channel MSs through linear precoder. Specifically, we first present a non-cooperative feedback-rate control game (NFC), in which each MS selects the feedback-rate to maximize its performance in a distributed way. To improve efficiency from a social optimum point of view, we then introduce pricing, called the non-cooperative feedback-rate control game with price (NFCP). The game utility is defined as the performance gain by CSI feedback minus the price as a linear function of the CSI feedback-rate. The existence of the Nash equilibrium of such games is investigated, and two types of feedback protocols (FDMA and CSMA) are studied. Simulation results show that by adjusting the pricing factor, the distributed NFCP game results in close optimal performance compared with that of the centralized scheme.

Optimal pilot design and placement for both the frequency offsets and channel estimation in Orthogonal Frequency-Division Multiplexing (OFDM) modulated Single Frequency Network (SFN) are treated in this paper. Unlike the conventional frequency-domain filter-based algorithms, the proposed pilot of each transmitter can always be demodulated even if the received pilots of multiple transmitters are totally overlapped. Although the channel state information (CSI) is needed in designing the proposed pilot for carrier frequency offset (CFO) estimation, the CFO estimation performance is robust to the channel estimation error. The optimal pilot as well as the Least-Squares (LS) channel estimator is also proposed, and the pilot for channel estimation is always constant-modulus. Simulation results demonstrate the performance of the proposed algorithm in terms of frequency offset and channel estimation errors. In SFN, some combining technologies such as equal gain combining (EGC) or maximal ratio combining (MRC) can be applied at the receiver to improve the receiving diversity gain. Numerical results show that in a scenario of two transmitters with a Signal-to-Noise Ratio (SNR) of 20 dB, the Bit Error Rate (BER) of 1.5 × 10-4(or 1 × 10-4) can be obtained by using EGC (or MRC), and the BER can be improved to be 4 × 10-6for EGC (or 2 × 10-6for MRC) by considering three co-receiver transmitters.

In the uplink of Orthogonal Frequency-Division Multiple Access (OFDMA) systems, the user carrier frequency offsets result in inter-carrier-interference (ICI) and multipleuser-interference (MUI), leading to a degradation of the bit error rate (BER). This paper treats this uplink scenario and derives the average uplink capacity and the BER using the signal-to-interference-and-noise ratio (SINR) analysis. Adaptive power allocation is suggested to increase the capacity. When the frequency offsets are modeled as zero-mean Gaussian or Uniform random variables, the BER is derived as a closed-form infiniteseries. The series requires at least 50 terms to ensure sufficient accuracy.

In cognitive radio networks, the secondary (unlicensed) users need to find idle channels via spectrum sensing for their transmission. Cooperative spectrum sensing (CSS) is a promising technology in spectrum sensing with an admirable performance. In CSS, multiple secondary users individually sense the idle channels and send their decisions to the network center, and then the center will do a final decision. In this paper, we focus on the optimal sensing settings of the CSS to maximize the channel throughput under some constraints on the interference to cognitive radio network. Particularly, we consider two scenarios in this paper. In the first scenario, only one channel is sensed at one time, and we aim at maximizing an individual channel capacity. Some simple algorithms are also derived to calculate the optimal solution for the first scenario. In the second scenario, multiple channels are jointly sensed simultaneously, and our objective is to maximize the overall channel capacity. We prove that the optimization problem in the second scenario can be converted into a convex-optimization problem, which can be solved efficiently and reliably. Simulation results show a significant improvement of the channel capacity by using the proposed optimal CSS in cognitive radio networks.

Frequency offset estimation for an orthogonal frequency-division multiple access (OFDMA) uplink for amplify-and-forward (AF) relays and a new type of relay (R) called decode-and-compensate-and-forward (DcF) relays are studied. Multiple relays are considered, and the relay with the best S rarr R channel is chosen to perform re-transmission, where S and R represent the source and relay nodes, respectively. Frequency offsets due to the mismatches between the transmitter and receiver oscillators are considered, and without considering the effect of Doppler shift, both S rarr D and S rarr R rarr D links have the same frequency offset, where D represents the destination. Thus, by using these two transmissions, D generates two frequency offset estimates, which are combined to minimize the mean square error (MSE). Power allocation between S and R can be adaptively adjusted to optimize the cooperative scheme in terms of frequency offset error variance. When channel state information (CSI) is available at each mobile node, a scheme where the relays adaptively switch between the cooperative and conventional (no relaying) transmissions is proposed to optimize the frequency offset estimation. Although the frequency offset estimation accuracy in the DcF mode is somewhat worse than the AF mode, both modes outperform the conventional transmission. However, DcF (or decode-and-forward (DF)) relays outperform AF relays in terms of channel capacity and bit error rate (BER).

In this paper, we evaluate the performance improvement in an Orthogonal Frequency-Division Multiple Access (OFDMA) uplink achievable with cooperative relaying in the presence of frequency offsets. We consider both the amplify- and-forward (AF) and decode-and-forward (DF) relays. In each transmission, each node plays two roles i.e., the source node and relay, simultaneously, but at different subcarriers. The proposed scheme improves performance without sacrificing the transmission rate and power of the cooperative relays, and the total power used to transmit each symbol, including the power consumed in node the source node and the relays, is kept constant. The outage information rates of the proposed cooperative transmission scheme are derived, and the diversity gain of each forwarding mode in an interference-limited environment is analyzed in this paper. Numerical results illustrate the superior performance of the proposed scheme over the conventional transmission with regard to outage information rate.

Optimal pilots design and placement for the frequency offset and channel estimation in orthogonal frequency- division multiplexing access (OFDMA) uplink systems are proposed. The received pilots of multiple users can always be demodulated, even if they are totally overlapped due to the large frequency offsets. With the knowledge of channel state information (CSI) at the receiver, the performance of the proposed frequency offset estimation is robust to the channel estimation errors. The frequency offset and CSI can be jointly estimated by employing the proposed pilots.

This paper discusses channel estimation in a cooperative orthogonal frequency-division multiplexing (OFDM) network in the presence of frequency offsets. Both the amplify- and-forward (AF) and decode-and-forward (DF) relaying modes are analyzed. In order to eliminate the multiple access interference (MAI), the maximum number of active AF and DF relays are [N/2L-1] and [N/L], respectively, where N is the total number of subcarriers, L is the channel order and [a] is the maximum integer part of a. The pairwise error probability (PEP) of orthogonal space-time coding in cooperative OFDM due to both the frequency offset and channel estimation errors is also evaluated. The optimal power allocation ratio between the source and the set of the relays to minimize the PEP is derived for both the relay modes. When L-3, and this gap increases to about 11.3 dB when the variance increases to 10-2.

This paper evaluates the performance improvement in orthogonal frequency-division multiplexing access (OFDMA) uplink frequency offset estimation achieved with cooperative relaying. The transmission of each source node (node S) can be improved by optimizing the diversity gain through exploiting the cooperation of the other nodes (cooperative relays), and the relays can operate in either the amplify-and-forward (AF) or decode-and-compensation-and-forward (DcF) mode. One or more than one geographically closely located mobile nodes comprise a cooperative group (CG), and the nodes of the same CG cooperate with each other. In each transmission, the role of the relay is to "help" the source node transmit its training sequence, or, in other words, the relay creates a parallel route between the source node and the destination terminal to improve the reliability of the transmission of S. In the proposed cooperative scheme, the total power used to transmit each training sequence, including that consumed in node S and the relay, is kept constant. Based on the interference analysis, the signal-to-interference-plus-noise ratio (SINR) in both the relay and the destination terminal are derived. The AF mode's cooperative scheme always outperforms that of the DcF mode in terms of frequency offset estimation accuracy due to the estimation error propagation in the latter.

Optimal pilot design and placement for channel estimation in multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems with frequency offsets are considered. Both the single-frequency- offset case and the multiple-frequency-offset case are treated. We show that the constant-envelope (CE) condition is sufficient but not necessary for pilot design, and that pilots with multiple envelopes can also achieve the optimal performance in terms of the mean square error (MSE) minimization, provided that an additional constraint on the pilot placement is satisfied simultaneously. New pilot designs, which take into account the multiple-frequency-offset case, are proposed to eliminate inter- pilot-interference (IPI) and to optimize the MSE performance. The least-squares (LS) and linear minimum mean square error (LMMSE) channel estimators for the multiple-frequency- offset case are designed for uncorrelated and correlated MIMO-OFDM channels, respectively. The LMMSE estimator requires the channel covariance matrix. Both optimal adaptive pilot power allocation and suboptimal uniform pilot power allocation are developed for the proposed LMMSE estimator. The adaptive allocation performs 4 dB better than the uniform allocation in the high noise region, but they both perform identically in the low noise region. Performance comparisons are made against several previous pilot designs due to [1], [2]. The proposed LMMSE estimator significantly outperforms the LS estimator.

Optimal pilot design and placement for channel estimation in multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems in the presence of frequency offset are discussed. Both the single-frequency-offset case and the multiple-frequency-offset case are treated. Constant-envelope (CE) is shown to be a sufficient but not necessary condition for optimizing the mean square error (MSE). When the CE condition is relaxed, i.e., pilots with multiple envelope values, the power allocation and placement rules for the optimal MSE performance are derived. The least-squares (LS) and linear minimum mean square error (LMMSE) estimators are designed for uncorrelated and correlated MIMO-OFDM channels, respectively. Both optimal adaptive pilot power allocation and suboptimal uniform pilot power allocation strategies are developed for the proposed LMMSE estimator. The adaptive allocation performs 4 dB better than the uniform allocation in the high noise region, but they both perform identically in the low noise region. Performance comparisons are made against several previous pilot designs due to [1]. The proposed LMMSE estimator significantly outperforms the LS estimator.

Since carrier frequency offset destroys user's signal orthogonality in orthogonal frequency-division multiplexing access (OFDMA) uplink transmission, resulting in an interference-limited system, its estimation/correction is very important. The residual carrier frequency offset of each user contributes inter-carrier-interference (ICI) and multiple-user-interference (MUI) to other users. In this paper, the effect of the carrier frequency offset on OFDMA uplink is analyzed. We first analyze the average uplink capacity losses as well as the signal-to-interference-and-noise ratio (SINR) reduction due to the carrier frequency offsets, and then discuss the capacity increases by using adaptive power allocation. The averaged bit error rate (BER) performance with the carrier frequency offsets on OFDMA uplink is also analyzed.

Performance analysis of multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems with carrier frequency offset and channel estimation errors is considered in this paper. Based on the analysis of the inter-carrier-interference (ICI) and inter-antenna-interference (IAI) due to the residual frequency offsets, the average signal-to-interference-and-noise ratio (SINR) is derived. The bit error rate of equal gain combining (EGC) and maximal ratio combining (MRC) with MIMO-OFDM is analyzed, and an infinite-series approximation for the bit error rate is derived. Simulation results illustrate the accuracy of the theoretical analysis.

In this paper, the authors derive the signal-to-interference-plus-noise ratio (SINR) for multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems in the presence of frequency offset and channel estimation errors. The channel is assumed to be frequency-selective Rayleigh fading. The analysis of the demodulated signal shows that the interference can be decomposed into two independent components: inter-carrier interference and interference contributed by other transmit antennas. The SINR for MIMO-OFDM systems with equal gain combining (EGC) and maximal ratio combining (MRC) are also derived.

A novel joint frame synchronization and carrier frequency offset estimation scheme for burst transmission mode multi-carrier systems is proposed, which uses a Central- Symmetric and Comb-Like training sequence (CSCL). This time-domain Comb-Like shape eases its power detection at the receiver without increasing the total training sequence power. Fine frame synchronization as well as carrier frequency offset acquisition with a maximum acquisition range of plusmnN/4timesSF times the subcarrier spacing can also be performed based on the proposed training sequence, where N denotes the Discrete Fourier Transform (DFT) length and SF stands for an integer-valued spreading factor that is used to generate the proposed training sequence. The remaining carrier frequency offset after acquisition can be further estimated and corrected by using a Fine Adjustment algorithm. In order to reduce the performance loss introduces by a higher Peak-to-Average Power Ratio (PAPR) in the CSCL, a time-domain Constant-Envelop training sequence (CE) is also proposed in this paper, which outperforms CSCL- based algorithm. The comparison of the proposed algorithms with the SS (Shi&Serpedin) algorithm by computer simulation illustrates the superior performance of the proposed algorithm with regard to estimation accuracy.

In orthogonal frequency-division multiplexing access (OFDMA) systems, multiple-user-interference (MUI) between different subscribers due to their non-zero carrier frequency offsets may deteriorate their BER performance greatly. Instantaneously large carrier frequency offset of one subscriber will contribute a heavy interference to its frequency-domain neighbors. MUI not only reduces the effective signal-to-interference-plus-noise ratio (SINR), but sometimes introduces a bias to carrier frequency offset estimators of each subscriber. In this paper, uplink carrier frequency offset estimation in OFDMA systems is discussed. The estimation accuracy of one estimator benefits from an effective MUI elimination/reduction. In the following sections, after analyzing the negative effect of MUI on uplink carrier frequency offset estimation, we will give out some interference reduction/elimination methods in OFDMA systems. Cramer-Rao lower bound (CRLB) for an unbiased carrier frequency offset estimator in a Multi-Access (MA) system is derived in this paper. A new training sequence group named round-robin training sequence group (RRTSG), is also proposed to perform uplink synchronization. It outperforms conventional training sequences with respect to higher interference mitigation/reduction capability

A new carrier frequency offset estimation scheme in orthogonal frequency-division multiplexing (OFDM) systems is proposed in this paper. Both the carrier frequency offset acquisition and tracking are based on a fixed-length training-symbol-block, which consists of multiple small identical training symbols. When each training symbol is shortened, the number of training symbols in the training-symbol-block should be increased accordingly to keep the total training-symbol-block length fixed. The proposed scheme extends Moose's estimator, where the estimation error is only dependent on total training symbol energy and cannot be reduced any more, once the total training symbol energy is determined. The proposed scheme can shorten each training symbol in a training-symbol block and select an appropriate estimator simultaneously, which can lead to further reduction of estimation error and increase of acquisition range, even with the total training-symbol-block energy being fixed. Performance analyzes for the proposed scheme in both the additive white Gaussian noise channel (AWGN) and the multipath channel are also presented in this paper. All estimators in the proposed scheme are conditionally unbiased, and simulation results demonstrate that they can work well both in the multipath channel and in the AWGN channel.

One new joint frame synchronization and carrier frequency offset estimation method for orthogonal frequency-division multiplexing (OFDM) system is proposed. The same training-symbol-block (TSB) is needed for both frame synchronization and carrier frequency offset estimation. The carrier frequency offset estimation including acquisition and tracking, and acquisition can be further divided into preacquisition and fine acquisition. As soon as frequency offset acquisition finished, timing synchronization is also performed at the same time. The acquisition range is as large as one half of overall signal bandwidth. The theoretical variance error lower bound for our frequency offset tracking algorithm is also derived in this paper.