This paper investigates the integration of active reconfigurable intelligent surfaces (ARISs) with unmanned aerial vehicles (UAVs) in a mixed free-space optics radio frequency (FSO-RF) downlink communication system, enabling simultaneous lightwave information and power transfer (SLIPT). The proposed architecture addresses key challenges in UAV-based networks, including limited endurance and backhaul constraints, by allowing the UAV to harvest energy from the optical backhaul while transmitting RF signals enhanced via ARIS to ground users. The system design aims to maximize the minimum achievable rate among users by jointly optimizing the UAV’s beamforming strategy, 3D placement, ARIS reflection coefficients, optical ground station (OGS) transmit power and the power splitting (PS) ratio at the UAV. An alternating optimization framework is developed to decompose the resulting non-convex problem into efficiently solvable subproblems using inner approximation techniques. Simulation results confirm that the proposed approach significantly outperforms baseline schemes, such as passive RIS, fixed UAV deployment, and static PS configurations, delivering improved rate fairness and energy efficiency. These results demonstrate the potential of ARIS-assisted SLIPT-enabled UAVs to support robust and sustainable downlink communications in next-generation wireless networks.

In recent years, federated learning (FL), a promising machine learning technique, has drawn increasing attention. Unlike conventional methods that centralize data for model training, FL ensures the safety and confidentiality of data by enabling the model training process on intelligent devices. However, the unpredictable and continuously changing channel characteristics pose a significant challenge to the implementation of FL in wireless communication. Consequently, optimizing energy efficiency becomes crucial, particularly for devices with constrained power resources. In this study, we tackle the problem of minimizing the total energy consumption during the training phase of FL over a cell-free massive multiple-input multiple-output (CFMM) system assisted by intelligent reflecting surfaces (IRSs) composed of hardware-efficient passive elements. Based on the operation mode of user equipments (UEs) during the uplink phase, the proposed CFMM-IRS system is categorized into System I employing time division multiple access mode, and System II allowing simultaneous user operation. Distinct problems are formulated for these systems, aiming to minimize all UEs’ overall energy consumption. To deal with these non-convex complex problems, we propose an alternating optimization approach by transforming the original problems into three sub-optimal ones and designing iterative algorithms utilizing the inner approximation method. Extensive experiments show the effectiveness of the proposed alternating optimization approach when resolving the given complex problems, highlighting their superior performance compared to other benchmark algorithms. Finally, simulation results indicate that System II, with UEs operating in simultaneous mode and associated with the proposed alternating algorithm, achieves the best result in terms of energy efficiency.

WiFi sensing-based human pose estimation (HPE) has gained significant attention in the academic community due to its advantages over vision- and sensor-based methods, including nonintrusiveness, convenience, and enhanced privacy protection. However, most existing WiFi-based pose Estimators suffer from poor performance and lack robustness in the presence of random noise. To address these challenges, this article presents a novel HPE architecture comprising two key modules: 1) a Denoiser and 2) an Estimator. The Denoiser is based on an autoencoder structure, while the Estimator is based on a new convolutional neural network (CNN) called SDy-CNN, which is designed to dynamically focus on high-information subcarriers of orthogonal frequency division multiplexing signals. Additionally, Bayesian optimization is employed to fine-tune the architecture’s parameters for optimal performance flexibly. Experiments conducted on a comprehensive dataset, MM-Fi, demonstrate that the proposed architecture significantly outperforms existing state-of-the-art Estimators, achieving up to an 8.38% improvement in HPE accuracy in clean data scenarios and up to a 14% improvement in noisy data scenarios. It has also been proven to gain computational efficiency when being much faster than other methods.

Spectral efficiency (SE) and energy efficiency (EE) are crucial for next-generation wireless Internet of Things networks. Device-to-device (D2D) communications and sparse code multiple access (SCMA) are promising solutions to meet the high Quality of Service. This requires a proper interference management for an ultradense user system. Considering both resource and power allocation, we herein aim to optimize the SE and improve the EE. First, rate fairness is considered to assign SCMA codewords to both cellular and D2D users. Subsequently, we propose a beamforming design and power allocation algorithm for D2D communications underlaying downlink and uplink operation of cellular networks, wherein energy harvesting is involved as a simultaneous wireless information and power transfer to assist an SCMA network.

This paper investigates the combined benefits of full-duplex (FD) and cell-free massive multiple-input multiple-output (CF-mMIMO), where a large number of distributed access points (APs) having FD capability simultaneously serve numerous uplink and downlink user equipments (UEs) on the same time-frequency resources. To enable the incorporation of FD technology in CF-mMIMO systems, we propose a novel heap-based pilot assignment algorithm, which not only can mitigate the effects of pilot contamination but also reduce the involved computational complexity. Then, we formulate a robust design problem for spectral efficiency (SE) maximization in which the power control and AP-UE association are jointly optimized, resulting in a difficult mixed-integer nonconvex programming. To solve this problem, we derive a more tractable problem before developing a very simple iterative algorithm based on inner approximation method with polynomial computational complexity. Numerical results show that our proposed methods with realistic parameters significantly outperform the existing approaches in terms of the quality of channel estimate and SE.

In-band full-duplex (FD) operation is practically more suited for short-range communications such as WiFi and small-cell networks, due to its current practical limitations on the self-interference cancellation. In addition, cell-free massive multiple-input multiple-output (CF-mMIMO) is a new and scalable version of MIMO networks, which is designed to bring service antennas closer to end user equipments (UEs). To achieve higher spectral and energy efficiencies (SE-EE) of a wireless network, it is of practical interest to incorporate FD capability into CF-mMIMO systems to utilize their combined benefits. We formulate a novel and comprehensive optimization problem for the maximization of SE and EE in which power control, access point-UE (AP-UE) association and AP selection are jointly optimized under a realistic power consumption model, resulting in a difficult class of mixed-integer nonconvex programming. To tackle the binary nature of the formulated problem, we propose an efficient approach by exploiting a strong coupling between binary and continuous variables, leading to a more tractable problem. In this regard, two low-complexity transmission designs based on zero-forcing (ZF) are proposed. Combining tools from inner approximation framework and Dinkelbach method, we develop simple iterative algorithms with polynomial computational complexity in each iteration and strong theoretical performance guaranteed. Furthermore, towards a robust design for FD CF-mMIMO, a novel heap-based pilot assignment algorithm is proposed to mitigate effects of pilot contamination. Numerical results show that our proposed designs with realistic parameters significantly outperform the well-known approaches (i.e., small-cell and collocated mMIMO) in terms of the SE and EE. Notably, the proposed ZF designs require much less execution time than the simple maximum ratio transmission/combining.

In this paper, physical layer security is considered for cognitive radio networks using an unmanned aerial vehicle (UAV)-enabled jamming noise. In the studied model, a secondary transmitter sends confidential messages to a secondary receiver in the presence of an external eavesdropper (Eve), and the UAV acts as a friendly jammer that degrades the decoding capability of Eve. Therefore, resource allocation in such a network must jointly optimize the transmission power and UAV's trajectory to maximize the secrecy rate, while satisfying a given interference threshold at the primary receiver. The design problem is non-convex, and thus, global optimality is difficult to obtain. Aiming to solve this problem, we first transform it into a more tractable form, and then propose a successive convex approximation-based algorithm for its solutions. The proposed algorithm has a low computational complexity and is guaranteed to obtain at least a locally optimal solution of the original problem. Numerical results are provided to demonstrate the effectiveness of the proposed design, compared to the existing ones.

This paper investigates the coexistence of non- orthogonal multiple access (NOMA) and full-duplex (FD), where the NOMA successive interference cancellation technique is applied simultaneously to both uplink (UL) and downlink (DL) transmissions in the same time-frequency resource block. Specifically, we jointly optimize the user association (UA) and power control to maximize the overall sum rate, subject to user-specific quality-of-service and total transmit power constraints. To be spectrally-efficient, we introduce the tensor model to optimize the UL users' decoding order and the DL users' clustering, which results in a mixed-integer non- convex problem. For solving this problem, we first relax the binary variables to be continuous, and then propose a low-complexity design based on the combination of the inner convex approximation framework and the penalty method. Numerical results show that the proposed algorithm significantly outperforms the conventional FD-based schemes, FD-NOMA and its half-duplex counterpart with random UA.

This paper investigates the coexistence of non-orthogonal multiple access (NOMA) and full-duplex (FD) to improve both spectral efficiency (SE) and user fairness. In such a scenario, NOMA based on the successive interference cancellation technique is simultaneously applied to both uplink (UL) and downlink (DL) transmissions in an FD system. We consider the problem of jointly optimizing user association (UA) and power control to maximize the overall SE, subject to user-specific quality-of-service and total transmit power constraints. To be spectrally-efficient, we introduce the tensor model to optimize UL users’ decoding order and DL users’ clustering, which results in a mixed-integer non-convex problem. For practically appealing applications, we first relax the binary variables and then propose two low-complexity designs. In the first design, the continuous relaxation problem is solved using the inner convex approximation framework. Next, we additionally introduce the penalty method to further accelerate the performance of the former design. For a benchmark, we develop an optimal solution based on brute-force search (BFS) over all possible cases of UAs. It is demonstrated in numerical results that the proposed algorithms outperform the conventional FD-based schemes and its half-duplex counterpart, as well as yield data rates close to those obtained by BFS-based algorithm.

This paper considers a full-duplex (FD) multiuser multiple-input single-output system where a base station simultaneously serves both uplink (UL) and downlink (DL) users on the same time-frequency resource. The crucial barriers in implementing FD systems reside in the residual self-interference and co-channel interference. To accelerate the use of FD radio in future wireless networks, we aim at managing the network interference more effectively by jointly designing the selection of half-array antenna modes (in the transmit or receive mode) at the base station with time phases and user assignments. The first problem of interest is to maximize the overall sum rate subject to quality-of-service requirements, which is formulated as a highly non-concave utility function followed by non-convex constraints. To address the design problem, we propose an iterative low-complexity algorithm by developing new inner approximations, and its convergence to a stationary point is guaranteed. To provide more insights into the solution of the proposed design, a general max-min rate optimization is further considered to maximize the minimum per-user rate while satisfying a given ratio between UL and DL rates. Furthermore, a robust algorithm is devised to verify that the proposed scheme works well under channel uncertainty. The simulation results demonstrate that the proposed algorithms exhibit fast convergence and substantially outperform existing schemes.

Consider a full-duplex (FD) multiuser system where an FD base station (BS) is designed to concurrently serve both downlink and uplink users in the presence of half-duplex eavesdroppers (Eves). The target problem is to maximize the minimum secrecy rate (SR) among all legitimate users. A novel user grouping-based fractional time allocation is proposed as an alternative solution, where information signals at the FD-BS are accompanied by artificial noise to degrade the Eves' channels. The SR problem has a highly non-concave and non-smooth objective, subject to non-convex constraints due to coupling between the optimization variables. Nevertheless, we develop a path-following low- complexity algorithm, which involves only a simple convex program of moderate dimensions at each iteration. Numerical results demonstrate the merit of the proposed approach compared to existing well-known ones, i.e., conventional FD and FD non-orthogonal multiple access.

This paper considers device-to-device (D2D) communications underlaying an uplink cellular network that adopts sparse code multiple access technology. We aim to maximize the spectral efficiency for D2D links in a transmission block via a joint power and resource allocation subject to the quality-of-service requirements for both cellular user equipments and D2Ds. We propose a low-complexity two-phase algorithm based on heuristic search and inner approximation method to efficiently solve the problem.

Phased array antenna has the capability of controlling the phase of individual antennas and thus widely used in wireless power transfer to direct and focus the beam towards the target steering angle. In order to perform beamforming in a wireless power transfer system, the transmitter needs to send pilot signals so that the receiver can estimate the channel to determine optimal beamforming weights. The beamforming weights are then fedback to the transmitter to be applied to the phased array antenna. The amount of feedback generally increases with the number of elements in the phased array. In this paper, we propose a scheme to reduce the amount of feedback based on far-field approximation in line-of-sight (LOS) environment. We analyze the effect of simplified feedback on the beam pattern in the case of uniformly distributed linear array antenna and planar array antenna.

The authors investigate pilot contamination in a multicell massive multiple‐input multiple‐output system, in which the estimated channel state information (CSI) is significantly different from the real CSI. Pilot contamination is an obstacle to achievable rates for users. The authors first propose an uplink training strategy to limit the effect of intercell pilot contamination on channel estimation with low complexity. As a result, the downlink data rate through the reciprocal channels is significantly improved. However, as the conventional uplink training, this strategy suffers from intra‐cell pilot contamination when the length of pilots is smaller than the number of users in a cell, while increasing the length of pilots degrades the spectral efficiency. The authors, therefore, propose a pilot optimisation that can be incorporated into the proposed training strategy. Based on the minimum mean square error criterion, they derive a closed‐form equation to determine the optimal pilots for all users in a multicell system. The joint pilot optimisation and proposed uplink training strategy is found to outperform other schemes, especially when the number of users exceeds the length of pilots in a cell. Numerical results verify that the downlink achievable rate with the proposed training strategy and pilot optimisation outperforms that with conventional approaches.

We consider a full-duplex (FD) multiuser system where an FD base station (BS) is designed to simultaneously serve both downlink (DL) and uplink (UL) users in the presence of half-duplex eavesdroppers (Eves). The problem is to maximize the minimum (max-min) secrecy rate (SR) among all legitimate users, where the information signals at the FD-BS are accompanied with artificial noise to debilitate the Eves' channels. To enhance the max-min SR, a major part of the power budget should be allocated to serve the users with poor channel qualities, such as those far from the FD-BS, undermining the SR for other users, and thus compromising the SR per-user. In addition, the main obstacle in designing an FD system is due to the self-interference (SI) and co-channel interference (CCI) among users. We therefore propose an alternative solution, where the FD-BS uses a fraction of the time block to serve near DL users and far UL users, and the remaining fractional time to serve other users. The proposed scheme mitigates the harmful effects of SI, CCI, and multiuser interference, and provides system robustness. The SR optimization problem has a highly nonconcave and nonsmooth objective, subject to nonconvex constraints. For the case of perfect channel state information (CSI), we develop a low-complexity path-following algorithm, which involves only a simple convex program of moderate dimension at each iteration. We show that our path-following algorithm guarantees convergence at least to a local optimum. Then, we extend the path-following algorithm to the cases of partially known Eves' CSI, where only statistics of CSI for the Eves are known, and worst-case scenario in which Eves can employ a more advanced linear decoder. The merit of our proposed approach is further demonstrated by extensive numerical results.

In this paper, we propose a selective Gaussian approximation to reduce the complexity of message passing algorithm (MPA) detection for uplink sparse code multiple access (SCMA) systems with multiple antennas. A subset of resource nodes, associated with antennas and subcarriers, are selected and the conventional MPA detection based on maximum likelihood (ML) is applied to those nodes. For the remaining resource nodes, Gaussian approximation is performed instead of ML. We first propose a simple but efficient antenna-subcarrier selection algorithm, and then develop a method to combine the two MPA detection schemes based on ML and Gaussian approximation. Numerical results are presented to show that the proposed MPA detection scheme provides an efficient tradeoff between the performance and receiver complexity.

This paper considers a full-duplex system for a base station (BS) serving both uplink and downlink users simultaneously on the same frequency. A new design of the selection of the half-array antenna mode at the BS (transmit or receive mode) over the time phases and user assignments is proposed and its beamforming design and power allocation problem are optimized under the effect of both residual self- interference and co-channel interference. The aim is to maximize the overall sum rate subject to the users' quality of service requirements, which is formulated as a highly nonlinear function subject to non-convex constraints. To solve this non-convex problem, we propose an iterative low- complexity algorithm. Simulation results demonstrate that the proposed algorithm provides a fast convergence and substantially outperforms all existing schemes.

This paper aims to design linear precoders for signal superposition at the base stations of non- orthogonal multiple access multiple-input multiple-output multi-cellular systems to maximize the overall sum throughput subject to the users' quality-of-service requirements, which are imposed independently on the users' channel conditions. This design problem is formulated as the maximization of a highly nonlinear and nonsmooth function subject to nonconvex constraints, which is very computationally challenging. A path- following algorithm for its solution, which invokes only a simple convex problem of moderate dimension at each iteration, is developed. Generating a sequence of improved points, this algorithm converges at least to a local optimum. Numerical results are then provided to demonstrate its merit.

In this paper, we propose a cooperative approach to improve the security of both primary and secondary systems in cognitive radio multicast communications. During their access to the frequency spectrum licensed to the primary users, the secondary unlicensed users assist the primary system in fortifying security by sending a jamming noise to the eavesdroppers, while simultaneously protect themselves from eavesdropping. The main objective of this work is to maximize the secrecy rate of the secondary system, while adhering to all individual primary users' secrecy rate constraints. In the case of passive eavesdroppers and imperfect channel state information knowledge at the transceivers, the utility function of interest is nonconcave and involved constraints are nonconvex, and thus, the optimal solutions are troublesome. To address this problem, we propose an iterative algorithm to arrive at a local optimum of the considered problem. The proposed iterative algorithm is guaranteed to achieve a Karush-Kuhn-Tucker solution.

The throughput of users with poor channel conditions, such as those at a cell edge, is a bottleneck in wireless systems. A major part of the power budget must be allocated to serve these users in guaranteeing their quality-of-service (QoS) requirements, hampering QoS for other users, and thus compromising the system reliability. In non-orthogonal multiple access (NOMA), the message intended for a user with a poor channel condition is decoded by itself and by another user with a better channel condition. The message intended for the latter is then successively decoded by itself after canceling the interference of the former. The overall information throughput is thus improved by this particular successive decoding and interference cancellation. This paper aims to design linear precoders/beamformers for signal superposition at the base stations of NOMA multiple-input multiple-output multi-cellular systems to maximize the overall sum throughput subject to the users' QoS requirements, which are imposed independently on the users' channel conditions. This design problem is formulated as the maximization of a highly nonlinear and nonsmooth function subject to nonconvex constraints, which is very computationally challenging. Path-following algorithms for its solution, which invoke only a simple convex problem of moderate dimension at each iteration, are developed. Generating a sequence of improved points, these algorithms converge at least to a local optimum. Extensive numerical simulations are then provided to demonstrate their merit.

A communication system is considered consisting of a full-duplex multiple-antenna base station (BS) and multiple single-antenna downlink users (DLUs) and single-antenna uplink users (ULUs), where the latter need to harvest energy for transmitting information to the BS. The communication is thus divided into two phases. In the first phase, the BS uses all available antennas for conveying information to DLUs and wireless energy to ULUs via information and energy beamforming, respectively. In the second phase, ULUs send their independent information to the BS using their harvested energy while the BS transmits the information to the DLUs. In both the phases, the communication is operated at the same time and over the same frequency band. The aim is to maximize the sum rate and energy efficiency under ULU achievable information throughput constraints by jointly optimizing beamforming and time allocation. The utility functions of interest are nonconcave and the involved constraints are nonconvex, so these problems are computationally troublesome. To address them, path-following algorithms are proposed to arrive at least at local optima. The proposed algorithms iteratively improve the objectives with convergence guaranteed. Simulation results demonstrate that they achieve rapid convergence and outperform conventional solutions.

In this paper, we consider beamforming design for an underlay cognitive radio multiple-input single-output broadcast channel, where a pair of secondary users coexists with multiple primary receivers. There exist multiple malicious eavesdroppers who attempt to overhear the confidential messages from the secondary system. When the channel state information of the eavesdroppers can only be obtained in the statistical sense, we transform the constraint which results from the statistical information of the passive eavesdroppers into a linear matrix inequality and convex constraint. To improve the secrecy rate of the secondary system, we aim to design a jamming noise to degrade the eavesdroppers. The main objective of the design is to maximize the secrecy rate of the secondary system while satisfying all the interference power constraints at the primary users and per-antenna power constraint at the secondary transmitter. The original problem is a nonconvex program, which can be reformulated to a convex program by applying the rank relaxation method. To this end, we prove that the rank relaxation is tight and it can be efficiently solved. Moreover, to develop an efficient resource allocation scheme we transform the relaxed problem into an equivalent problem based on a duality result.

Pilot contamination reduction can improve the achievable uplink and downlink rates in a multicell massive multiple‐input–multiple‐output system. To this end, this study first proposes two schemes to mitigate the effect of pilot contamination by implementing uplink training with time‐aligned and time‐shifted pilot transmissions. Accordingly, these techniques enable the system not only to exploit the advantages of time‐shifted training but also to benefit from the use of conventional systems that improve the achievable rates. The authors introduce channel estimation in matrix form by estimating from a near minimum mean square error method. Furthermore, linear detector and precoding methods are used for a base station with a finite number of antennas in order to derive the closed‐form lower bounds of the achievable rates with two uplink training schemes for both uplink and downlink transmissions. Finally, numerical results are presented to verify the analysis.

In this paper, we consider the secure beamforming design for an underlay cognitive radio multiple-input single-output broadcast channel in the presence of multiple passive eavesdroppers. Our goal is to design a jamming noise (JN) transmit strategy to maximize the secrecy rate of the secondary system. By utilizing the zero-forcing method to eliminate the interference caused by JN to the secondary user, we study the joint optimization of the information and JN beamforming for secrecy rate maximization of the secondary system while satisfying all the interference power constraints at the primary users, as well as the per-antenna power constraint at the secondary transmitter. For an optimal beamforming design, the original problem is a nonconvex program, which can be reformulated as a convex program by applying the rank relaxation method. To this end, we prove that the rank relaxation is tight and propose a barrier interior-point method to solve the resulting saddle point problem based on a duality result. To find the global optimal solution, we transform the considered problem into an unconstrained optimization problem. We then employ Broyden-Fletcher-Goldfarb-Shanno method to solve the resulting unconstrained problem, which helps reduce the complexity significantly, compared with the conventional methods. Simulation results show the fast convergence of the proposed algorithm and substantial performance improvements over the existing approaches.

In this paper, we proposed a symbiotic approach for a secure primary network by allowing the secondary users to send the jamming noise to degrade the wiretap ability of the eavesdropper. In particular, assuming that the global channel state information is perfectly known at tranceivers, we consider the case of the primary transmitter equipped with only one antenna, which implies that the primary transmitter does not have beamforming capability. As the reward of having access to the frequency spectrum which is licensed by the the primary user, the secondary transmitter will assist the primary systems in terms of security by sending the jamming noise to the eavesdropper. We propose an algorithm to find the optimal transmit power for maximizing the secrecy capacity of the primary system. Numerical results are presented to validate our proposed scheme.

In this paper, we propose an improved cognitive radio (CR) model in which the secondary system can harvest energy from the primary system and access the spectrum of the primary system to transmit its own data in an underlay mode. This model exploits the benefit of spatial diversity at the destination of the secondary system by selecting a best relay among multiple decode-and-forward (DF) relays. The outage probability of the secondary network is evaluated as a function of the maximum transmit power at the secondary transmitter (ST) under a constraint of peak interference power at the primary receiver (P R), the energy harvesting period at ST, the path loss for the channels between primary and secondary networks. The numerical results are presented to show significant improvement in the performance of the secondary system.

In this paper, the performance of opportunistic relay selection (ORS) in a cognitive radio is analyzed over flat Rayleigh fading channels. Data transmission between source and destination is assumed to be entirely performed via the relays. Relay nodes are assumed to have ability to harvest energy from the source signal and use that harvested energy to forward the information to the destination. Specifically, we derive an exact expression for the outage probability of the secondary system considering the maximum transmit power at the secondary transmitter and relays, energy harvesting efficiency at relays, and interference constraint at the primary receiver. Under the assumption of perfect channel state information at the receivers, we evaluate the outage probability of a cognitive radio system with ORS and energy harvesting.

Device-to-Device (D2D) communication has become an important technology in future networks, since it can provide advantages such as cell throughput enhancement, user equipment power saving, and increased instantaneous data rate. However, the performance of both D2D and cellular communication can be affected by mutual interferences between them. In this paper, we analyze a resource allocation method for D2D links underlaying cellular networks. A novel method which allows more than one D2D pair to reuse the downlink resource of one cellular user is proposed. In addition, we also present an algorithm to assign a cellular user to each group of D2D pairs, when there are a number of cellular users and D2D users. The proposed algorithm is designed to guarantee that the SINR for both the cellular link and D2D link exceeds acceptable thresholds.

In this paper, we propose an inter-cell interference management scheme using a multi-cell SRN (Shared Relay Node) in order to avoid inter-cell interference and to increase the cell throughput in 3GPP LTE (3rd Generation Partnership Project Long Term Evolution)-Advanced networks. Recently, the CoMP (Coordinated Multi-Point transmission/reception) scheme has received growing attention as a promising scheme for overcoming the inter-cell interference in 3GPP LTE-Advanced networks. In practice, however, when feedback delays and channel estimation errors are considered, the performance of the CoMP scheme may severely degrade. The objective of this paper is to present a new SRN architecture located at the neighboring area of adjacent cells so as to manage the inter-cell interference. The SRN can overhear control signals transmitted by adjacent eNBs (enhanced Node-B) and UEs (User Equipments). Based on the overheard information, the SRN not only performs data retransmission as a usual type II relay but also manages the inter-cell interference. In particular, we suggest a resource allocation scheme and a power control scheme assisted on the SRN for effective interference avoidance, and evaluate their performances through simulations.

As a scheme to efficiently reduce the effects of multipath fading in next generation wireless communication systems, cooperative communication systems have recently come into the spotlight. Since these cooperative communication systems use cooperative relays with diverse fading coefficients to transmit information, having all relays participate in cooperative communication may result in unnecessary waste of resources, and thus relay selection schemes are required to efficiently use wireless resources. In this paper, we propose an efficient relay selection scheme through self-learning in cooperative wireless networks using Q-learning algorithm. In this scheme, we define states, actions and a reward to achieve good SER (Symbol Error Rate) performance, while selecting a small number of cooperative relays. When these parameters are well-defined, we can obtain good performance. The simulation results show that, compared to a scheme that obtains optimum numbers of relays through a mathematical analysis, the proposed scheme uses resources efficiently by using smaller numbers of relays with comparable SER performance. In particular, whereas the number of cooperative relays linearly increases as the number of relays that can participate increases in the case of the scheme modeled by a mathematical analysis, the proposed scheme selects 2.5 relays on average for cooperative communication. According to these simulation results, the proposed scheme can be considered as a good attempt for future communication.

We present an effective scheme for preventing eavesdropping in wireless communication systems. In the proposed scheme, the modulation scheme is designed to change based on an expanded signal constellation, in such a way that the eavesdropper cannot be aware of the change. As compared to previously proposed schemes that rely on specific relay nodes, the proposed scheme is advantageous in that it can keep the transmit messages secure without requiring any assistance of relays.

In this paper, we propose an efficient channel feedback algorithm for network MIMO systems that selects the proper number of channels for feedback among the whole channels observed by each user and allocates unequal number of feedback bits to the users. The proposed algorithm considers a limited feedback scenario, in which the channel state information is conveyed from the user to the base station in the form of quantized vector index. Through computer simulations, it is confirmed that the proposed algorithm provides significant performance improvement over previously proposed schemes in terms of the average sum rate.

In this paper, a feedback channel selection scheme and a bit allocation scheme are proposed for a network MIMO system with limited feedback. The feedback channel selection is performed by comparing the gain of each channel vector with a certain threshold. In particular, we derive an optimal threshold that maximizes a utility function, which is defined in terms of the expected rate of each user. In addition, we also develop an unequal feedback bit allocation scheme over the selected set of channels to further improve the system performance. It is shown that the joint feedback channel selection and bit allocation can provide significant gain in the average sum rate for a network MIMO system with limited feedback.

We propose an interference-aware user selection scheme for uplink multiuser multiple-input multiple-output (MU-MIMO) systems in a multicell environment. The proposed scheme works in a distributed manner. Each mobile station (MS) determines its transmit beamforming vector based on the locally available channel state information (CSI), and informs the associated base station (BS) of the amount of potential interference caused to adjacent cells along with the resulting beamforming vector. Then, the BS selects a set of users to be served simultaneously with consideration of intercell interference. The user selection scheme is devised either to maximize the sum rate or to achieve proportional fairness among users. For each case, we derive an optimal user selection criterion and propose a suboptimal distributed user selection algorithm with low complexity. Simulation results confirm that the proposed scheme offers significant throughput enhancement due to reduction of the intercell interference in a multicell environment.

The authors propose a full-duplex relay (FDR) based on a block diagonalisation (BD) method in multiple-input multiple-output (MIMO) relay channels. The BD method is employed to suppress the self-interference in MIMO FDR as well as to transmit multiple data streams to multiple users at the same time. The authors also derive the optimal power allocation strategy for MIMO FDR operation. Numerical results show that the use of the proposed FDR with BD can provide enhanced system performance compared with the FDR with zero-forcing beamforming.

We propose a new cognitive beamforming scheme for coexistence of IR (incumbent radio) CR (cognitive radio). The proposed cognitive beamforming scheme does not cause any interference to the IRU (IR User), while the CRU (cognitive radio user) is served without additional radio resource consumption. Simulation results show that when using the proposed scheme the CRU does not interfere to the IRU and there is little bit error rate performance degradation of the CRU as compared to that of the ideal beamforming system which does not consider the IR priority.

In mobile WiMAX systems, uplink collaborative MIMO (multiple input multiple output) performs spatial multiplexing with two PSSs (portable subscriber stations), each with one antenna. As two PSSs transmit collaboratively on the same sub-channel, the overall uplink capacity will be doubled. To perform this interesting technique with high performance, most system venders demand the optimal MLD (maximum-likelihood detection) in the RAS (radio access station). However, the MLD is difficult to implement due to its explosive computational complexity. In this paper, we propose a two-step MIMO decoding scheme which achieves near ML performance with low complexity for CSM (collaborative spatial multiplexing) in uplink mobile WiMAX systems that having an iterative channel decoder using bit LLR (log-likelihood ratio) information. Simulation results show that the proposed scheme has almost the same BLER (block error rate) performance of the MLD with only about 15.75% computational complexity in terms of real multiplication, when both PSSs transmit with 16 QAM (quadrature amplitude modulation) modulation.

Uplink multiple-input multiple-output (MIMO) transmission scheme is developed for time division duplex (TDD) systems in a multicell environment. We propose a precoding scheme that maximizes the total achievable rate and works in the decentralized manner with only locally available channel state information (CSI) at each transmitter. We first establish and solve a decentralized optimization problem for the case of multiple-input single-output (MISO) channels, introducing a new precoding design metric called signal to generated interference plus noise ratio (SGINR). By extending the result to general MIMO channels, we propose an SGINR-based precoding scheme where the number of transmit streams is selected adaptively to the surrounding environments. Simulation results confirm that the proposed precoding scheme offers significant throughput enhancement in multicell environments.

Multiple-input multiple-output (MIMO) precoding scheme is developed for time division duplex (TDD) systems in a multicell environment. The proposed scheme is designed to maximize the total achievable rate, and to work in the decentralized manner with only locally available channel state information (CSI) at each transmitter. We first establish and solve a decentralized optimization problem for the case of multiple-input single-output (MISO) channels. We introduce a new precoding design metric called signal to generating interference plus noise ratio (SGINR). Based on the SGINR metric, the MISO precoding scheme is extended to general MIMO channels. Simulation results confirm that proposed precoding scheme offers significant throughput enhancement in multicell environments.

In this paper, we construct a family of block orthogonal Golay sequences that have low peak-to-mean envelope power ratio (PMEPR) as well as block wise orthogonal properties. We then present an application of the sequences to channel estimation of multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. We compare the performance of the proposed algorithm with that of a frequency division multiplexing (FDM) piloting algorithm, and investigate the effect of co-channel interference (CCI) on the channel estimation performance.

Various hybrid duplexing techniques have been proposed to accommodate asymmetric multimedia services for next generation cellular systems. Many of them apply time division duplexing (TDD) technology in the inner cell region and frequency division duplexing technology in the outer region. One concern for such arrangement would be mitigating the intercell interference. They need, however, to use a fairly long guard time between uplink and downlink portion of a frame, because of the propagation time from the base station (BS) to the farthest mobile station (MS) in the TDD region. Such inefficiency becomes exaggerated when the raw data rate increases. We propose a multi-layer TDD architecture which includes several concentric TDD regions having different guard times. The proposed architecture has been proven by computer simulation that it has much smaller average delay when there is a mixture of multimedia traffic, and it accommodates more traffic having with different requirements of maximally allowable delay.

We propose a set of distributed rate control algorithms for the reverse-link of CDMA systems using a pricing mechanism. In the derivation, we assume that the base station broadcasts a real-valued feedback in order to control the reverse activity level. In addition, we assume that the access terminals are able to transmit data at any rate within a finite range, and that the transmission power is a linear function of the transmission rate. For a specific utility function, we show that the proposed algorithm achieves social optimality, satisfies an interference power constraint, and exhibits desirable short- and long-term fairness behaviors. We then modify this algorithm so that it can be applied to the case when the transmission power is a convex function of the transmission rate. Next, we consider the case that the feedback parameter is a single reverse activity bit, and the underlying rates are elements of a discrete set of admissible rates. This scenario is similar to that of the IS-856 standard. We further modify our algorithms so that they can be applied to this system setup, and verify the performance using numerical simulations. It is demonstrated that our algorithms exhibit short- and long-term fairness behavior for this realistic scenario.

We propose a new distributed rate control algorithm for the reverse link of CDMA systems. Specifically, when the statistics of packet arrivals are known locally to each access terminal (AT), this new algorithm aims to provide a means to control the relative delay that each AT experiences. For this algorithm, assuming that the arrival process is Poisson and stationary, it is shown through simulations that all ATs experience an equal amount of average delay when the system is underloaded, and the same packet drop probability when the system is over-loaded. Furthermore, we propose a modification to the algorithm that gives priority to some desired ATs, and reduces their relative average delay. Finally, simulation results indicate that the algorithm achieves similar short-term average delay even when the packet arrival process is not stationary.

We propose a quality of service (QoS) management framework and a packet scheduling scheme over a shared wireless link for heterogeneous classes of traffic. The QoS management framework is developed based on the characterization of different QoS requirements of heterogeneous traffic classes. The framework comprises two subsequent packet scheduling modules and load control modules. Based on the QoS management framework, we propose an effective packet scheduling scheme that accounts for the wireless channel, status of packet queues, the degree of QoS satisfaction, and fairness among sessions. Simulation results show that the proposed packet scheduling scheme provides better performance than the previously proposed schemes in light or moderate system load, and that it provides fair sharing of QoS degradation in overload.

In this letter, we present a modification of Vertical Bell Laboratories Layered Space-Time (V-BLAST), and propose an effective transmit power allocation (TPA) scheme for the modified system. The proposed TPA scheme minimizes the uncoded bit-error rate (BER) averaged over all detection stages, and requires small feedback overhead. Simulation results show that the modified V-BLAST system with the proposed TPA scheme provides a significant reduction in the uncoded BER compared with the conventional V-BLAST system. When the minimum mean-square error nulling is adopted, the modified V-BLAST system is found to achieve the uncoded BER performance comparable to that of the maximum-likelihood detection for the conventional V-BLAST architecture.

The use of differentially coherent combining is proposed to improve the performance of a double-dwell acquisition system by increasing the reliability of a decision in the verification stage. The detection and mean acquisition time performance of the acquisition scheme with the proposed combining scheme is analyzed in frequency-selective Rayleigh fading channels, and compared with that of two previously published double-dwell acquisition schemes based on long correlation intervals and noncoherent combining. It is shown that the proposed acquisition scheme outperforms the previous ones, and that the performance improvement increases as the frequency offset increases.

A generalized code acquisition scheme for direct-sequence code-division multiple-access systems with multiple antennas is proposed over frequency-selective fading channels. The proposed scheme is developed on the framework of a generalized configuration of multiple antennas and correlators. The nonconsecutive search method is generalized and extended to multiple antenna systems to exploit multipath signals in improving acquisition performance over frequency-selective fading channels. The proposed scheme also adopts a hybrid decision strategy to make effective decisions on acquisition. The mean acquisition time performance of the proposed acquisition scheme is analyzed and evaluated in frequency-selective Rayleigh-fading channels with general multipath delay profiles and spatial-fading correlations. The effects of nonconsecutive search on mean acquisition time are investigated for various channel environments, and the optimal choice of decision strategy is discussed. Furthermore, effects of various configurations of multiple antennas and correlators, decision thresholds, and correlation interval on the performance are also investigated.

A generalized acquisition scheme is proposed for direct sequence code-division multiple-access systems with multiple antennas. The proposed scheme employs grouping of multiple antennas as a means of a tradeoff between two important factors determining the mean acquisition time, combining gain and search time. The performance of the proposed acquisition scheme is analyzed in frequency-selective Rayleigh-fading channels with consideration of spatial correlations. Numerical results show that the use of the largest number of antenna groups is preferable to reducing the mean acquisition time at low signal-to-interference ratio (SIR) values. At high SIR values, on the contrary, the mean acquisition time is found to increase in proportion to the number of antenna groups. In a typical environment, the presence of spatial correlation is shown to increase or decrease the mean acquisition time within 50% compared with the uncorrelated fading case.

A code acquisition scheme is proposed for DS/CDMA systems with multiple antennas. The proposed scheme employs a new search scheme, referred to as sparse search, to utilize multipath signals in reducing mean acquisition time over frequency-selective fading channels. The mean acquisition time performance of the proposed scheme is analyzed and evaluated in frequency-selective Rayleigh fading channels. The performance of the proposed scheme is compared with that of the conventional one. Numerical results show that the proposed acquisition scheme outperforms the conventional one, and that the performance improvement becomes greater as the number of resolvable paths increases. The effects of configuration of multiple antennas and receiver complexity on mean acquisition time are also investigated.

The effective use of multiple antennas is investigated for code acquisition. A generalized acquisition scheme is proposed for DS/CDMA systems with multiple antennas. The proposed scheme provides means of a trade-off between two important factors determining the mean acquisition time, which are referred to as combining gain and search time, respectively. The performance of the proposed acquisition scheme is analyzed in frequency-selective Rayleigh fading channels. In the analysis, the effects of spatial fading correlations on acquisition performance are considered. The mean acquisition time performance is evaluated for various environments, and the configuration of multiple antennas is investigated to reduce the mean acquisition time. The effects of spatial correlation on mean acquisition time are also investigated. The mean acquisition time is found to decrease significantly as the number of antenna elements increases. It is found that various parameters such as the number of antenna elements, operating signal-to-interference ratio (SIR), and the number of resolvable paths should be considered in determining configuration of multiple antennas to reduce mean acquisition time.

The use of differentially coherent combining is proposed to improve the performance of a double-dwell acquisition system. The differentially coherent combining is employed to increase the reliability of a decision in the verification stage. The mean acquisition time performance of the acquisition scheme with the proposed combining scheme is analyzed in a Rayleigh fading channel and compared with that of a conventional double-dwell acquisition scheme with noncoherent combining. It is shown that the proposed acquisition scheme outperforms the conventional one, and that the performance improvement increases as the frequency offset increases.

Slot synchronization is a critical step for fast and reliable cell search in intercell asynchronous direct sequence-code division multiple access systems. To increase reliability, observations over a number of slots may be combined. In this paper, combining schemes of multiple observations are studied for slot synchronization. The optimal combining rule is determined based on detection theory. It is found that two known combining schemes correspond to special cases of the optimal combining. These schemes may not work well in typical environments, since the schemes are optimized for specific environments. To improve slot synchronization performance in typical environments, a new combining scheme is proposed. The performance of the proposed combining scheme as well as other combining schemes is analyzed for Rayleigh fading channels with frequency offset. Numerical analysis shows that the proposed combining scheme significantly outperforms other combining schemes in typical environments.

The performance of frequency-hopping spread-spectrum systems employing noncoherent reception and transmission diversity is analyzed for frequency-selective Rayleigh fading channels. Two different types of transmission diversity systems, a fast frequency-hopping (FFH) system and a multicarrier frequency-hopping (MCFH) system, are investigated. In order to combine received signals from transmit diversity channels, the optimum diversity combining rule based on the maximum-likelihood criterion is developed. Probability of error equations are derived, and utilized to evaluate the performance of the two systems. The MCFH systems are found to outperform FFH systems when the channel delay spread is severe, while FFH systems are superior to MCFH systems when a channel varies rapidly. Furthermore, it is found that performance enhancement due to an increase of diversity order is more significant for MCFH systems than for FFH systems in frequency-selective fading channels. The effect of frequency-selective fading is also investigated in determining optimum frequency deviations of binary frequency-shift keying signals.

A novel acquisition scheme that utilizes multipaths to improve the acquisition performance is proposed for frequency-selective fading channels. The proposed acquisition scheme employs nonconsecutive search and joint triple-cell detection. The performance is analyzed in frequency-selective Rayleigh fading channels. Equations for the probabilities of detection and false alarm are derived, and an expression for the mean acquisition time is developed. The mean acquisition time performance of the proposed and conventional acquisition schemes is evaluated and compared. It is found that the proposed acquisition scheme significantly outperforms the conventional one. The effects of various channel parameters such as the number of resolvable paths, the shape of the multipath intensity profile (MIP) and the signal-to-interference ratio (SIR) on acquisition performance are also investigated.

Slot combining is a method to achieve fast code acquisition in inter-cell asynchronous DS/SS systems by employing multiple observations. The optimal slot combining is difficult to implement, since it requires information on channel and frequency offset. Two practical combining schemes, a noncoherent combining and a coherent combining, are found to be special cases of the optimal combining. In this paper, a novel differentially coherent combining scheme is proposed. This combining scheme may be viewed as a combination of differential detection and coherent combining techniques. The performances of the differentially coherent combining as well as the optimal combining, noncoherent combining, and coherent combining are analyzed for Rayleigh fading environments with frequency offset. It is found that the differentially coherent combining scheme significantly outperforms the noncoherent combining and coherent combining schemes for a typical range of Doppler spread and frequency offset.

A novel acquisition scheme that utilizes multipaths to improve the acquisition performance is proposed for frequency-selective fading channels. The proposed acquisition scheme employs nonconsecutive search with joint triple-cell detection. The performance of the proposed acquisition scheme is analyzed in frequency-selective Rayleigh fading channels, and compared with that of the conventional one. The proposed acquisition scheme is found to significantly outperform the conventional one. The effects of various channel parameters on the acquisition performance are also investigated.