Magnetic induction (MI) communication is an effective underground emergency communication technique after disasters such as landslides, mine collapses, and earthquakes, due to its advantages in mediums such as soil, concrete, and metals. However, the propagation mediums in practical MI based underground emergency communications are usually diverse and composed randomly due to the impact of disasters, which poses a challenge for MI communication in practical applications. In this paper, we formulate a statistical fading channel model, which reflects the random composition of diverse mediums and is shown to follow a lognormal distribution. To mitigate the impact of diverse medium fading, Multi-frequency Resonating Compensation (MuReC) based coils are used to achieve multi-band transmission. Then, we analyze the performance of MuReC based multi-band MI communication with diverse medium fading and derive the expressions of signal-to-noise ratio (SNR) probability density functions, ergodic capaciteis, average bit error rates (BERs), and outage probabilities for both multiplexing and diversity cases. Numerical results show that MuReC based multi-band transmission schemes can effectively reduce the impact of diverse medium fading and enhance the performance.

In virtual reality (VR) applications, 360° images are crucial for delivering immersive and panoramic experiences. However, the substantial data volumes create significant challenges for network storage and bandwidth. Additionally, transmission channel noise can further degrade the user experience by introducing visual distortions. To address these challenges, in this paper we propose a condensed semantic communication framework, specifically the channel denoising-based latent consistency model (CDLCM), designed for efficient 360° image transmission. The CDLCM compresses transmission data by employing deep neural networks (DNNs) to extract multiscale semantic features, which are then condensed via vector quantization (VQ). While this approach reduces transmission overhead, it may result in the loss of crucial image details and increase vulnerability to noise. To counteract these effects, the CDLCM integrates a spherical attention mechanism to detect and correct VQ errors caused by noise during inverse quantization. Additionally, the latent consistency model (LCM) iteratively denoises and restores lost image details, ensuring high-quality reconstruction. The framework also adapts to estimated channel noise by dynamically adjusting the diffusion steps to improve computational efficiency. Numerical experiments verify that the CDLCM not only reduces transmission overhead but also achieves superior reconstruction quality for 360° images compared to state-of-the-art methods. Overall, CDLCM offers an effective solution that balances compression efficiency and reconstruction fidelity, making it well-suited for immersive 360° image transmission.

In this paper, we propose a virtual full-duplex (VFD) technique with zero-interval modulation and sampling (ZIMS), where two half-duplex (HD) transceivers can simultaneously transmit signals and each transceiver can effectively receive the desired information. In ZIMS-VFD, the transceiver inserts a zero-interval for each symbol in the transmit signal and provides self-interference (SI)-free intervals for itself. Meanwhile, it samples the receive signal in the provided SI-free intervals and restores the desired symbols. Based on orthogonal frequency division multiplexing (OFDM), we formulate the system model and show the transmit signal structure. Then, we give the transceiver design for single input single output (SISO) ZIMS-VFD and extend it to multiple input multiple output (MIMO) communications. Numerical results verify our theoretical analyses and show that ZIMS-VFD can effectively increase the capacity and approach the FD without SI.

The development of orbital angular momentum (OAM)-based radio vortex transmission presents a promising opportunity for increasing the capacity of wireless communication in correlated channels due to its inherent orthogonality among different OAM modes. One of the most popular schemes for high-efficient OAM transmission is the digital baseband associated with uniform circular array (UCA) based transceiver. However, the periodicity of complex-exponential feed makes the maximum number of orthogonal signals carried by multiple OAM modes generally restricted to the array-element number of UCA antenna, which poses an open question of how to employ more OAM modes given a fixed number of array elements. Furthermore, signals modulated with high-order OAM modes are difficult to be captured by the receiver due to their serious divergence as propagating in free space, thus severely limiting the capacity of radio vortex communications. To overcome the above challenges, in this paper based on the partly element-overlapped fractal geometry layout and effectively using low-order OAM modes, we propose the quasi-fractal UCA (QF-UCA) antenna based OAM multiplexing transmission. We perform the two-dimension OAM modulation (TOM) and demodulation (TOD) schemes with the orthogonal OAM mode number exceeding the array-element number, which is beyond the traditional concept of multiple antennas based wireless communications. Simulation results show that our proposed scheme can achieve more number of orthogonal multiplexing streams than the maximum number of orthogonal multiplexing corresponding to traditional multiple antenna systems.

Magnetic induction (MI) communications have gained substantial attention due to the advantages in special environments such as underground, underwater, and human body. MI wireless networks in such environments can enable important applications in future civil and public security fields. However, due to the particularity of application environments, it is challenging to guarantee the energy supply for MI devices. In this paper, we propose a backscatter based bidirectional full-duplex MI communication (BFMC), which can enhance the energy efficiency of MI communications. In BFMC, additional information is backscattered with the inherent backscatter property of MI channel and the backscatter device (BD) is free of self-interference (SI). For the BFMC based multi-user network, we formulate the joint magnetic beamforming and time allocation optimization problem, which aims to minimize the average energy consumption and guarantee the downlink signal to noise ratio (SNR), uplink signal to interference plus noise ratio (SINR), and energy harvesting requirements. The formulated problem is non-convex and transformed into magnetic beamforming and time allocation sub-problems. Based on block coordinate descent (BCD) method, the sub-problems are solved iteratively. Numerical results show that BFMC and the proposed joint beamforming and time allocation scheme can effectively reduce average energy consumption and enhance energy efficiency.

In this paper, we investigate the joint beamforming design for access and fronthaul links in a user-centric network with full-duplex fronthaul. We formulate an optimization problem to maximize the network energy efficiency while guaranteeing fronthaul rate requirements. Particularly, the power consumed by self-interference cancellation at full-duplex access points (APs) is taken into consideration to comprehensively reflect the effect of full-duplex technology. Due to the non-convexity and the nonlinear fractional form of the formulated problem, we resort to the successive convex approximation method. The original problem is approximated as a convex second-order cone program. We then extend the study to the scenario of imperfect and partial channel state information (CSI). To avoid the intractable expression of the achievable rate in this case, we derive its lower bound for further beamforming design. Simulation results demonstrate the superiority of the proposed algorithm in terms of energy efficiency and power consumption under both CSI scenarios. For our considered full-duplex fronthaul networks, moderate maximum transmit power of macro base station (MBS) and APs is sufficient to obtain desired energy efficiency performance. Moreover, the lower bound is verified to be tight at the low-maximum power region.

Magnetic Induction (MI) based transmissions, where the typical applications are wireless power transfer (WPT) and MI communications, have gained substantial attention in recent years. Existing works related to MI based transmissions mainly focus on the case with single resonant frequency. However, from the perspective of practical applications, it is highly demanded to achieve multi-frequency access for MI based transmissions. Although multiple coils can be used to generate additional resonant frequencies, each coil is often with one resonant frequency. In this paper, we develop the Multi-frequency Resonating Compensation (MuReC) coil based Multiple-band, Multiple-Input, and Multiple-Output (MbMIMO) simultaneous wireless information and power transfer (SWIPT), which can generate multiple resonant frequencies with one coil. The access point (AP) is equipped with multiple MuReC coils as well as delivers power and data to single-coil receivers (RXs) with different resonant frequencies. We propose the magnetic beamforming scheme for MuReC-MbMIMO-SWIPT, which aims to minimize the transmit power as well as guarantee the network throughput, total delivered power, and individual requirements of each channel. The beamforming schemes for two special cases of MuReC-MbMIMO-SWIPT, that is, MuReC-MbMIMO-communications and MuReC-MbMIMO-WPT, are also given. The optimal beamforming scheme in closed-form for MuReC-MbMIMO-communications is derived. In addition, the parameter design scheme for MuReC coils, which can support an arbitrary number of resonant frequencies, is developed. Numerical results verify our theoretical analyses and show that MuReC-MbMIMO transmissions and the proposed beamforming schemes can fully use antenna resources and effectively support multi-frequency access.

This letter addresses the time-of-arrival based localization problem when the source and sensors are not synchronized, whereby an unknown transmission time is introduced. A non-convex weighted least squares (WLS) minimization problem is first formulated to jointly estimate the source position and the unknown transmission time by transforming the measurement model, and then semidefinite relaxation is applied to relax the WLS problem as a convex semidefinite program (SDP). The relaxed SDP problem is always tight and thus the optimal solution of the WLS problem can always be obtained. The proposed method is then extended to the moving source localization scenario, where the source velocity is assumed to be a constant for a sufficiently small observation period. Simulation results show that the proposed method is able to reach the Cramer-Rao lower bound accuracy when the noise is not very large.

Owing to the spatial orthogonality, orbital angular momentum (OAM), which describes the helical phase fronts of electromagnetic waves, shows an extensive application prospect for increasing the spectrum efficiency and enhancing the physical layer security of wireless communications. However, efficient anti-jamming results of existing mode hopping (MH) schemes are achieved with pre-shared hopping sequences. Such MH schemes require the strict synchronization between the legitimate transmitter and receiver, thus leading to complex system design. Also, pre-shared hopping sequences greatly limit the MH application scenarios. To solve the problem of no pre-shared hopping sequences between the legitimate transmitter and receiver for anti-jamming, in this paper we propose the precoding-based mode hopping (PoM) scheme. Specifically, we design the transmitter by dividing the input information into the index information and signal information. Based on the index information, the activated OAM-modes for hopping and the phase shift for precoding are determined. OAM-mode and phase shift randomization make jammers difficult to disrupt the communication. Then, the receiver with OAM decomposition and phase shift decoding is designed to extract legitimate signals. Also, the lower bound of achievable rate for our proposed PoM scheme is derived. Numerical results show that our proposed PoM scheme is superior to the conventional index-modulation based mode division multiplexing (IM-MDM) schemes in terms of achievable rate under hostile jamming.

In this paper, we investigate an energy-efficient beamforming design in a user-centric full-duplex backhauling network, where simultaneous transmission and reception on the same frequency band for access and backhaul links are enabled by full-duplex access points. Specifically, multicast transmission is adopted by macro base station and cooperative transmission is adopted by access points to serve users. We first formulate an optimization problem to maximize the network energy efficiency while taking the power consumed by self-interference cancellation at full-duplex access points into consideration. This problem is formulated as a nonlinear fractional programming and is transformed into an equivalent subtractive form by Dinkelbach method. The equivalent optimization problem is still non-convex. To make it more tractable, we first adopt semidefinite relaxation to remove part of non-convexity, and then adopt the successive convex approximation method to further deal with the rest of non-convex parts, and finally propose an iterative algorithm. Simulation results demonstrate the superiority of the proposed algorithm and provide insights into the design of full-duplex backhauling network.

Integrating Network Function Virtualization (NFV) into Multi-Access Edge Computing (MEC) network has been proposed. In the NFV-enabled MEC network, Service Function Chains (SFCs) are proposed to orchestrate Virtual Network Functions (VNFs) required by Network Service Requests (NSRs) for adapting to the various NSRs. NSRs are initiated as a set of requests for VNFs, and those requests should be mapped onto specific VNF instances in the executing-order, which also means embedding dependence-aware SFCs into the physical network. It is extremely challenging to optimize the latency when embedding SFCs into the MEC network because the executing-order constraint of VNFs in SFCs causes trouble for measuring the latency of designed SFC embedding schemes. For these reasons, we investigate how to minimize the latency when embedding SFCs into the heterogeneous MEC network under the condition of considering the dependency and concurrency of VNFs. Above all, a resource management model based on graph theory, element graph, is proposed to express the dependency of various resources in the NFV-enabled MEC network, which overcomes the problems caused by heterogeneity. Furthermore, relying on graph theory, we propose a universal evaluating model that can flexibly measure the latency cost of any designed service chain. Depending on the element graph and evaluating model, the Genetic Algorithm (GA) is adopted to optimize the latency of embedding SFCs, which can adaptively orchestrate the optimal VNFs for any SFC to minimize the latency.

Since the relatively low frequency band has been extensively used, the design paradigm is shifted to the high frequency band such as the promising millimeter wave (mmWave) band in the fifth generation (5G) beyond and the expected terahertz in the sixth generation (6G). Due to the severe electromagnetic degradation for high frequency band, line-of-sight (LOS) transmission for short-range high-speed scenarios has been receiving much attention. In this paper, we introduce the nonplanar electromagnetic waves (NEWs) based wireless communications, which can provide a considerable enhancement for channel capacity. After giving a brief definition of the NEWs, a specific case of the NEWs which is based on the Zadoff-Chu (ZC) phase shift matrix is proposed and analyzed. This kind of NEWs is non-hollow with its orthogonal beams sharing the same radiation pattern except with different rotations along the azimuth. Simulation results are given to validate the capacity enhancement and analyze the robustness performance of NEWs based wireless communications.

In this paper, we investigate the resource allocation problem for a full-duplex network with machine-to-machine devices and cellular users. Our objective is to maximize the network sum rate while achieving individual quality-of-service (QoS) requirements, considering imperfect and partial channel state information. The sum rate maximization problem is formulated as a mixed-integer nonlinear programming problem. We decouple it into a subcarrier assignment subproblem and a power allocation subproblem to make it more tractable. The non-convex subcarrier assignment problem is transformed to a convex problem by applying majorization minimization method, and then solved by the interior-point method. While the power allocation problem is solved by applying the Lagrange dual method. Simulation results demonstrate the impact of channel estimation error on sum rate performance and the superiority of the proposed algorithm. Furthermore, the fairness is improved among users by QoS guarantee.

Low earth orbit (LEO) satellite network has the advantages of comprehensive coverage and has the unique benefits of short satellite-to-ground transmission distance and low construction cost, which can effectively complement the limited coverage of ground mobile communication network. Hence, LEO satellites gain extensive attention in the field of mobile communication. However, restricted by the existing mode (BP, Bent Pipe) of high transmission latency problems in the LEO space satellite computing (LSSC), it is challenging to meet the low latency requirement of time-sensitive tasks. Therefore, on-orbit collaborative computing technology for LSSC is proposed in this paper. While due to the high dynamic and non-centrality of the LEO satellite system, collaborative computing in satellite networks will face many difficulties. Aiming at the high dynamic and non-centrality of the LEO satellite network, this paper proposes a dispersed computing paradigm for the LEO satellite network, which is suitable for high dynamic no-center scenarios. In this dispersed computing paradigm, a steady-state matrix based on the time-expanded graph (TEG) model is introduced in this paper to steady-state the topology of a high dynamic LEO satellite network. According to the matrix, a transmission capacity and computing capacity based diffusion algorithm (TCGDA) is proposed to perform optimal task allocation in the LEO satellite network. The simulation results show that the proposed dispersed computing method can effectively complete the computing task with the optimized latency.

Abstract This paper presents a time slot‐split non‐orthogonal multiple access (TSS‐NOMA) scheme for full‐duplex (FD) cooperative communication systems to improve resource utilisation. Aiming at the problem of low bandwidth efficiency when pairing users, TSS‐NOMA divides a complete time slot into several parts to improve the pairing process. Users can occupy all bandwidths in different slots to reduce the waste of bandwidth resources. Unlike the scheme of forwarding a single signal, TSS‐NOMA decodes the information symbols of relay, and re‐encodes the messages through the new power allocation factors of successfully paired users. The hybrid symbols are sent to increase the proportion of central users' own signals received by themselves, thus improving the ergodic capacity of the system. To maximise the minimum achievable rate of the system, TSS‐NOMA optimises the power allocation at the base station, and the relay. The performance of TSS‐NOMA is verified by simulation, where numerical results show that this scheme can achieve higher spectral, and energy efficiency.

For unforeseen natural disasters, such as earthquakes, hurricanes, and floods, etc., the traditional communication infrastructure is unavailable or seriously disrupted along with persistent secondary disasters. Under such circumstances, it is highly demanded to deploy emergency wireless communication (EWC) networks to restore connectivity in accident/ incident areas. The emerging fifth-generation (5G)/beyond-5G (B5G) wireless communication system, like unmanned aerial vehicle (UAV) assisted networks and intelligent reflecting surface (IRS) based communication systems, are expected to be designed or re-farmed for supporting temporary high quality communications in post-disaster areas. However, the channel characteristics of post-disaster areas quickly change as the secondary disaster resulted topographical changes, imposing new but critical challenges for EWC networks. In this paper, we propose a novel heterogeneous$\mathcal {F}$composite fading channel model for EWC networks which accurately models and characterizes the composite fading channel with reflectors, path-loss exponent, fading, and shadowing parameters in 5G-UAV based EWC networks. Based on the model, we develop the optimal power allocation scheme with the simple closed-form expression and the numerical results based optimal joint bandwidth-power allocation scheme. We derive the corresponding capacities and compare the energy efficiency between IRS and traditional relay based 5G-UAVs. Numerical results show that the new heterogeneous Fisher-Snedecor$\mathcal {F}$composite fading channel adapted resource allocation schemes can achieve higher capacity and energy efficiency than those of traditional channel model adapted resource allocation schemes, thus providing better communications service for post-disaster areas.

To enhance spectrum efficiency for the future Internet-of-Things, in this paper, we investigate the joint subcarrier and power allocation problem for a full-duplex network with machine-to-machine nodes and cellular nodes. We aim to maximize the network spectral efficiency while achieving individual quality-of-service (QoS) requirements, considering imperfect and partial channel state information. The spectral efficiency maximization problem is formulated as a mixed-integer nonlinear programming problem and proved to be NP-hard. To make it more tractable, we first solve the coupling between subcarrier assignment and power allocation variables by replacing the product of two variables with one auxiliary variable. We then relax the binary subcarrier assignment variables to integer variables and introduce penalty terms to penalize the objective function. Majorization minimization method is adopted to further handle the coupling between uplink and downlink due to full-duplex transmission. We prove that the proposed joint resource allocation scheme converges to local optimal solution. Simulation results demonstrate the impact of channel estimation error on spectral efficiency and the superiority of the proposed algorithm.

Unmanned aerial vehicles (UAVs) have been widely used to provide enhanced information coverage as well as relay services for Internet of Things (IoT). Constrained by the limited computation and battery capabilities of IoT devices, computational-intensive tasks are difficult to be tackled locally. In this paper, a UAV-aided mobile edge computing (UAMEC) system is constructed to assist IoT devices to tackle computational-intensive tasks. Furthermore, we jointly optimize communications, computing and caching resources allocation strategies for the sake of maximizing the net revenue from the UAMEC under the condition of guaranteeing user's quality of experience (QoE). A multi-dimensional hybrid adaptive particle swarm (MHAPSO) algorithm is conceived to solve this joint optimization problem. Finally, the effectiveness and superiority of our proposed scheme are demonstrated.

Orbital angular momentum (OAM), which is considered as a novel way to achieve high capacity, has been attracted much attention recently. OAM signals emitted by uniform circular array (UCA) are widely treated as going through the Bessel-form channels. However, the channel gains corresponding to the Bessel-form channels are with low signal-to-noise-ratio (SNR) on OAM-modes and it is difficult to achieve high capacity using all OAM modes. To achieve maximum capacity offered by OAM multiplexing for wireless backhaul communications, in this paper we propose the optimal UCA design, which selects the optimal OAM-modes and radius of receive UCA. We formulate the capacity maximization problem and divide it into two subproblems for obtaining the corresponding optimal UCA design for OAM multiplexing based wireless backhaul communications. In particular, the optimal radius of the receive UCA is firstly derived. Then, we propose a mode selection scheme to choose appropriate OAM-modes for data transmission to maximize the capacity. Extensive simulations obtained validate that the capacity of OAM multiplexing can be significantly increased with our developed scheme.

Internet of Vehicles (IoV) has drawn great interest recent years. Various IoV applications have emerged for improving the safety, efficiency, and comfort on the road. Cloud computing constitutes a popular technique for supporting delay-tolerant entertainment applications. However, for advanced latency-sensitive applications (e.g., auto/assisted driving and emergency failure management), cloud computing may result in excessive delay. Edge computing, which extends computing and storage capabilities to the edge of the network, emerges as an attractive technology. Therefore, to support these computationally intensive and latency-sensitive applications in IoVs, in this article, we integrate mobile-edge computing nodes (i.e., mobile vehicles) and fixed edge computing nodes (i.e., fixed road infrastructures) to provide low-latency computing services cooperatively. For better exploiting these heterogeneous edge computing resources, the concept of software-defined networking (SDN) and edge-computing-aided IoV (EC-SDIoV) is conceived. Moreover, in a complex and dynamic IoV environment, the outage of both processing nodes and communication links becomes inevitable, which may have life-threatening consequences. In order to ensure the completion with high reliability of latency-sensitive IoV services, we introduce both partial computation offloading and reliable task allocation with the reprocessing mechanism to EC-SDIoV. Since the optimization problem is nonconvex and NP-hard, a heuristic algorithm, fault-tolerant particle swarm optimization algorithm is designed for maximizing the reliability (FPSO-MR) with latency constraints. Performance evaluation results validate that the proposed scheme is indeed capable of reducing the latency as well as improving the reliability of the EC-SDIoV.

Orbital angular momentum (OAM) based mode hopping (MH) scheme is expected to be a potential anti-jamming technology in radio vortex wireless communications. However, it only uses one OAM-mode for hopping, thus resulting in low spectrum efficiency (SE). Index modulation offers a trade-off balance between the SE and performance reliability. In this paper, we propose an MH with OAM-based index modulation scheme, where several OAM-modes are activated for hopping, to achieve high SE at a given bit error rate in radio vortex wireless communications. Based on the proposed scheme, we derive the upper bound and lower bound of achievable SEs. Furthermore, in order to take advantage of index information, we derive the optimal hopped OAM-modes to achieve the maximum SE. Numerical results show that our proposed MH with index modulation scheme can achieve high SE while satisfying a certain reliability of radio vortex wireless communications.

Orbital angular momentum (OAM) has attracted much attention for radio vortex wireless communications due to the orthogonality among different OAM-modes. To maintain the orthogonality among different OAM modes at the receiver, the strict alignment between transmit and receive antennas is highly demanded. However, it is not practical to guarantee the transceiver alignment in wireless communications. The phase turbulence, resulting from the misaligned transceivers, leads to serious intermode interference among different OAM modes and therefore fail for signals detection of multiple OAM modes at the receiver. To achieve practical OAM based wireless communications, in this paper we investigate the radio vortex wireless communications with misaligned transmit and receive antennas. We propose a joint Beamforming and Pre-detection (BePre) scheme, which uses two unitary matrices to convert the channel matrix into the equivalent circulant matrix for keeping the orthogonality among OAM-modes at the receiver. Then, the OAM signals can be detected with the mode-decomposition scheme at the misaligned receiver. Extensive simulations obtained validate and evaluate that our developed joint BePre scheme can efficiently detect the signals of multiple OAM-modes for the misaligned transceiver and can significantly increase the spectrum efficiency.

Due to the limited computing resources of swarm of drones, it is difficult to handle computation-intensive tasks locally, hence the cloud based computation offloading is widely adopted. However, for the business which requires low latency and high reliability, the cloud-based solution is not suitable, because of the slow response time caused by long distance data transmission. Therefore, to solve the problem mentioned above, in this paper, we introduce fog computing into swarm of drones (FCSD). Focusing on the latency and reliability sensitive business scenarios, the latency and reliability is constructed as the constraints of the optimization problem. And in order to enhance the practicality of the FCSD system, we formulate the energy consumption of FCSD as the optimization target function, to decrease the energy consumption as far as possible, under the premise of satisfying the latency and reliability requirements of the task. Furthermore, a heuristic algorithm based on genetic algorithm is designed to perform optimal task allocation in FCSD system. The simulation results validate that the proposed fog based computation offloading with the heuristic algorithm can complete the computing task effectively with the minimal energy consumption under the requirements of latency and reliability.

In this paper, a power allocation space-time coding scheme based on self-coding of residual loop interference (RLI) for two-way full-duplex (FD) amplify-and-forward (AF) relaying networks is proposed. In the proposed scheme, the relay first realizes a distributed space-time code by performing self-coding using the RLI at relay node after implementing some self-interference cancellation techniques. Then power allocation is performed between the terminals. With the proposed power allocation scheme, both amplifying factor and transmit powers of terminal nodes are jointly optimized under a total power constraint when estimated instantaneous channel state information is available. Simulation results show that the proposed scheme achieves performance improvement in an FD relaying system.

Orbital angular momentum (OAM), which is inherently possessed by the electromagnetic (EM) beams, bridges a new way for multiple access using multiple orthogonal OAM-modes in wireless communications. Uniform circular array (UCA), as a convenient antenna structure for supporting the transmission and reception of OAM based signals, has been paid much attention in recent years. However, the OAM beams generated by the UCAs are centrally hollow and divergent, limiting the efficient reception as well as the long-distance transmission for OAM based signals. To solve this problem, in this paper we propose the Zadoff-Chu (ZC) sequence based scrambling scheme to generate the non-hollow OAM beams while maintaining the orthogonality among different OAM-modes. Then, based on the properties of applying discrete Fourier transform (DFT) for circulant matrices and zero-free sequences, we develop the scrambling-tolerant detection scheme to efficiently obtain the transmit symbols. Performance evaluations show the non-hollow irregular OAM beams and validate that our developed ZC sequence based scrambling scheme works well for long-distance transmission in OAM based wireless communications.

Industrial Internet of Things (IIoT) is a revolution which is changing the visage of industry in a profound manner. However, it brings many opportunities as well as many puzzles and challenges. Facing with billions of programmable IIoT devices, the traditional IIoT architecture based on cloud computing is no longer suitable, therefore, Mobile Edge Computing (MEC) has been seen as the promising technology to support IIoT business in 5G era. However, the existing mainstream MEC framework exposes numerous problems when supporting IIoT, such as complex development, low development reuse rate, poor software maintainability and mobility, poor flexibility, etc. Therefore, in order to solve the problems mentioned above, in this paper, we propose IIoT-MEC, a novel MEC framework specially for IIoT. We use Docker container to slice computing and storage resources of MEC server into numerous resource blocks (RBs). Based on the concept of virtualization, some RBs for “Device Function Virtualization (DFV)” are used to map physical devices into virtual devices and present in a set of normalized APIs, which shield the hardware development of diverse IIoT devices, so as to simplify the IIoT development into software development only. Some RBs are used to support the operation of IIoT services, in the form of distributed computing. On these basis, a flexible object-oriented IIoT development architecture is constructed. IIoT-MEC can overcome the drawbacks of the existing MEC framework in supporting IIoT. And the implementation procedure of IIoT-MEC is demonstrated with an application example. We also discuss how the IIoT-MEC would be used and what we need to do in future research.

With the vigorous development of vehicular communications in 5G and beyond networks, cognitive satellite-terrestrial networks are expected to support multitudinous services and applications in future intelligent transportation systems and mobile Internet. To this aim, we introduce a cognitive satellite-vehicular network (CSVN) in this paper, where the secondary vehicular communications are featured with mobility. To realize friendly coexistence between satellite and vehicular networks as well as efficient resource utilization, we investigate the tradeoff between energy efficiency (EE) and spectrum efficiency (SE) and analyze the associated power allocation in the CSVN. Specifically, by introducing a preference factor which reflects the priority level of EE/SE, we firstly propose a unified EE-SE tradeoff metric to adapt to dynamic vehicular environments. Based on the formulated EE-SE tradeoff metric, we derive a power allocation strategy under the interference power constraints imposed by primary satellite communications. Finally, simulation results are provided to show the effects of preference factor, interference constraints, and vehicle velocity on the EE-SE tradeoff performance.

This study focuses on spectrum sensing under Laplacian noise. To mitigate the negative effects caused by the heavy‐tailed behaviour of Laplacian noise, the fractional lower order moments (FLOM) technology is employed to pre‐process the received samples before spectrum sensing. Through exploiting the asymmetrical difference between the distribution for the FLOM of received samples in the absence and presence of primary users, the authors formulate the spectrum sensing problem under Laplacian noise as a unilateral goodness‐of‐fit (GoF) test problem. Based on this test problem, they propose a new GoF‐based detector, which is called a unilateral left‐tail Anderson Darling (ULAD) detector. The analytical expressions for the theoretical performance, in terms of false‐alarm and detection probabilities, of the ULAD are derived. Moreover, a closed‐form expression for the optimal detection threshold is also derived to minimise the total error rate. Simulation results are provided to validate the theoretical analyses and to demonstrate the superior performance of the proposed detector than others.

In ultra‐dense networks (UDNs), the interference management constitutes a great challenge due to the densely deployed base stations (BSs) and the traffic fluctuating with time. To tackle this challenge, the authors propose a cross‐tier cooperation load‐adapting interference management (CCLA‐IM) scheme in UDNS, which employs three technologies to mitigate inter‐cell interference (ICI) efficiently. Firstly, fractional frequency reuse technology is employed to coordinate the ICI among macro BSs (MBSs) as well as the ICI between MBSs and small BSs (sBSs). Secondly, they use load‐adapting resource allocation technology to mitigate ICI further when the sBSs traffic is partially loaded. Thirdly, the interference‐aware resource allocation can mitigate ICI further by optimising the physical resource blocks mapping methods. The simulation results show that the proposed CCLA‐IM can achieve considerable performance gain in system spectral efficiency, the throughput of sBSs, system energy efficiency and ICI distribution while the density of sBSs and the traffic are changing with time.

This letter focuses on the design of an optimal resource allocation scheme to maximize the energy efficiency (EE) in a simultaneous wireless information and power transfer (SWIPT) enabled two-way decode-and-forward (DF) relay network under a non-linear energy harvesting model. In particular, we formulate an optimization problem by jointly optimizing the transmit powers of two source nodes, the power-splitting (PS) ratios of the relay, and the time for the source-relay transmission, under multiple constraints including the transmit power constraints at sources and the minimum rate requirement. Although the formulated problem is non-convex, an iterative algorithm is developed to obtain the optimal resource allocation. Simulation results verify the proposed algorithm and show that the designed resource allocation scheme is superior to other benchmark schemes in terms of EE.

Wireless network virtualization, which decouples the physical supply process and the service provisioning process, can abstract, isolate, and share the physical infrastructure network equipment. This paper studies the resource virtualization in virtual multiple-input multiple-output single-carrier frequency-division-multiple-access uplink systems, where resources are abstracted to hide the complex details of the fading channel and the link rates are virtualized using the statistical method. Furthermore, the virtual link rates are scheduled and instantiated to different slices with customized delay-bounded quality of service (QoS) provisioning. In this scheme, a physical mobile network operator (PMNO) is in charge of the network resource at the physical layer, while virtual mobile network operators (VMNOs) are responsible for the traffic admission and the slice management at the MAC layer. Furthermore, we build up the resource virtualization problem as a cross-layer Stackelberg game, which has the interactive dual processes based on the QoS exponent: top-to-down sub-game of leaders at the MAC layer and down-to-top sub-game of follower at the physical layer. Using the newly designed functions for PMNO and VMNOs, we develop an effective dynamic algorithm with an iterative dual update to meet the optimization targets of PMNO and VMNOs. Simulation results verify the superiority and stability of delay-bounded QoS guaranteed wireless resource virtualization algorithm developed in this paper in terms of convergence, access rate, and delay-outage probability.

This paper proposes a novel design of cooperative non-orthogonal layered multicast multiple access in a heterogeneous network, where the information is encoded into the messages of high priority (HP) and low priority (LP). Two types of multicast users coexist in the network: 1) regular users (RUs), which are located far away from the base station (BS) and expect to decode only the HP message (due to the weak channels), and 2) advanced users (AUs), which are located close to the BS and expect to decode both HP and LP messages. To improve the reliability of layered multicast, we consider that the successful AUs (those AUs who successfully decode the HP and LP messages) serve as potential relays to assist other AUs/RUs. Based on this idea, two novel cooperation strategies are proposed for different cases of channel information availability. For each proposed strategy, we derive closed-form exact outage probabilities of AUs and RUs and then further analyze their diversity orders. Moreover, considering that the layered multicast is outage-constrained, we theoretically evaluate the energy consumption of both strategies and demonstrate their energy saving gains over the direct non-orthogonal multiple access for layered multicast. Finally, our theoretical analysis is verified by numerical results, and the advantages of the proposed strategies are also demonstrated.

With the ever increasing spectrum demand of broadband multimedia services, cognitive satellite terrestrial networks have emerged as a promising paradigm for future space information networks. To provide services with diverse delay quality-of-service (QoS) requirements in an energy-limited system, in this paper, we investigate energy efficient power allocation for cognitive satellite terrestrial networks. Employing statistical delay-QoS metric, power allocation schemes are formulated as optimization problems to maximize effective energy efficiency of secondary satellite communications while satisfying interference constraints imposed by primary terrestrial communications. Specifically, allowing for the availability of instantaneous channel state information (CSI) of the secondary transmitter-primary receiver link, optimal transmit powers are derived for both the cases of statistical and instantaneous interference constraints. Moreover, to provide a theoretical insight on the performance of the considered network, we derive closed-form expressions for the outage probability based on the obtained optimal transmit powers. The simulation results demonstrate the validity of the theoretical results and show the impacts of the delay exponent, interference constraint, and aggregate interference from terrestrial networks on the performance of satellite networks.

Orbital angular momentum (OAM) based radio vortex wireless communications have the potential to significantly increase the spectrum efficiency (SE) without increasing extra time and frequency resources. In this paper, we propose a hybrid orthogonal division multiplexing (HODM) scheme, which jointly uses the orthogonal mode division multiplexing and the conventional orthogonal frequency division multiplexing (OFD-M) to increase the SE of radio vortex wireless communications. In particular, we develop the mode and frequency dimensions based two-dimension inverse fast Fourier transform (2D-IFFT) algorithm at the transmitter to modulate transmit signal and two-dimension fast Fourier transform (2D-FFT) algorithm at the receiver to demodulate received signal, respectively. Then, we propose an optimal power allocation scheme to maximize the SE of our proposed HODM scheme. Numerical results show that the HODM scheme can significantly increase the SE in comparison with the conventional OFDM schemes.

Simultaneous wireless information and power transfer (SWIPT) has been recognized as a promising approach to improving the performance of energy constrained networks. In this paper, we investigate a SWIPT based three-step two-way decode-and-forward (DF) relay network with a non-linear energy harvester equipped at the relay. As most existing works require instantaneous channel state information (CSI) while CSI is not fully utilized when designing power splitting (PS) schemes, there exists an opportunity for enhancement by exploiting CSI for PS design. To this end, we propose a novel heterogeneous PS scheme, where the PS ratios are dynamically changed according to instantaneous channel gains. In particular, we derive the closed-form expressions of the optimal PS ratios to maximize the capacity of the investigated network and analyze the outage probability with the optimal dynamic PS ratios based on the non-linear energy harvesting (EH) model. The results provide valuable insights into the effect of various system parameters, such as transmit power of the source, source transmission rate, and source to relay distance on the performance of the investigated network. The results show that our proposed PS scheme outperforms the existing schemes.

This paper proposes a novel design of cooperative non-orthogonal multiple access (NOMA) for layered multicast, where the information is encoded into the messages of high-priority (HP) and low-priority (LP). Two types of multicast users coexist in the system: 1) regular users (RUs), which locate far away from the base-station (BS) and demand only the HP message; 2) advanced users (AUs), which locate close to the BS and demand both HP and LP messages. To improve the reliability of layered multicast, an opportunistic cooperative NOMA multicast strategy is proposed, in which one successful AU is selected to forward both HP and LP messages. For the proposed strategy, we derive closed-form exact outage probabilities of AUs and RUs. By further carrying out the asymptotic analysis, the achieved diversity orders are shown to be not less than the number of AUs, i.e., full diversity is achieved. Finally, numerical results verify the theoretical analysis and demonstrate the superiority of the proposed strategy.

The plane wave based wireless communications have becoming more and more matured, along with the well utilization of the traditional resources such as time and frequency. To further increase the capacity for rapidly increasing capacity demand of wireless communications, it is potential to use the twist wave, which has the orbital angular momentum (OAM). In this paper, we discuss the OAM based wireless communications in the aspect of orthogonality, degree of freedom (DoF), and capacity, where both the transmitter and the receiver use uniform circular array (UCA) antennas. In particular, we compare OAM based wireless communications with multiple-input-multiple-output (MIMO) based wireless communications in terms of DoF and capacity. Numerical results are presented to validate and evaluate that the DoF of OAM based wireless communications is greater than or equal to that of correlated MIMO based wireless communications when the transmitter and the receiver antennas are aligned well. The OAM based wireless communications can achieve larger capacity than the correlated MIMO in high signal-to-noise ratio (SNR) region under line-of-sight scenario.

Orthogonal frequency division multiplexing (OFDM), which has attracted much attention during the past few decades, can be used for not only anti-multipath but also high spectrum efficiency in wireless communications. However, as the spectrum becoming more and more crowded and the amount of traffic eventually increasing, it is very difficult to increase the spectrum efficiency in wireless communications. Recently, orbital angular momentum (OAM), which provides a novel mode dimension, offers the potential to achieve high spectrum efficiency for wireless communications. In this paper, we propose the orthogonal mode division multiplexing (OMDM) scheme for high capacity in wireless communications. In particular, we propose to transmit half-integer and integer OAM-modes signals within two narrowbands to avoid the inter-mode interference. Second, we propose the mode inverse fast Fourier transform (M-IFFT) algorithm at the transmitter to modulate signals and mode fast Fourier transform (M-FFT) algorithm at the receiver to demodulate signals, respectively. Finally, we develop the dynamic power allocation scheme to solve the problem of how to maximize the capacity of OMDM. Numerical results show that our developed OMDM scheme can achieve high capacity. Furthermore, we can jointly use our developed OMDM scheme with the conventional OFDM scheme to increase the capacity of wireless communications.

Recently, the industrial Internet of Things (IIoT) has drawn high attention in academia and industry in the context of industry 4.0. In the IIoT, smart IoT devices are adopted to improve production efficiency. But, these devices will generate huge amounts of production data, which need to be processed effectively. To support IIoT services efficiently, cloud computing is usually considered as one of the possible solutions. However, the IIoT services still suffer from the high-latency and unreliable links problem between cloud and IIoT terminals. To combat these issues, fog computing is a promising solution which extends computing and storage to the network edge. In this paper, we are motivated to integrate the fog computing to the cloud-based IIoT to build a cloud-fog integrated IIoT (CF-IIoT) network. To achieve the ultra-low service response latency, we introduce the distributed computing to the CF-IIoT network and propose leveraging the real-coded genetic algorithm for constrained optimization problem(RCGA-CO) algorithm to optimize the load balancing problem of the distributed cloud-fog network. Most importantly, considering the unreliable situation in the CF-IIoT (e.g., fog nodes damage, wireless links outage), we propose a task reallocation and retransmission mechanism to reduce the average service latency of the CF-IIoT network architecture. The performance evaluation results validate that the RCGA-CO-based CF-IIoT and our proposed mechanism can provide ultra-low latency service in IIoT scenario.

In this study, the authors study the power efficiency optimisation in wireless‐powered full‐duplex relay (WFR) systems, where the entire transmission process can be partitioned into wireless power transfer phase (WP) and full‐duplex information transmission phase (FP). For WFR systems with same source transmit power, where the source transmit powers of WP and FP are same, they first prove that the power efficiency is a strictly concave function over the time‐switching factor, and an optimal time allocation scheme is proposed to maximise the power efficiency. Then, for the given time‐switching protocol, the optimal power allocation strategy is obtained by analysing the derivative of the power efficiency with respect to the transmit power. Finally, they propose the joint power and time allocation scheme. For WFR systems with different source transmit power, where the source transmit powers of WP and FP are different, the optimal time allocation scheme and optimal power allocation strategy are derived by studying the derivative of the power efficiency. Furthermore, the joint power and time allocation scheme is proposed to maximise the power efficiency. Simulation results are presented to validate the authors' proposed schemes for the WFR systems.

Non‐orthogonal multiple access (NOMA) has been proposed as a promising technique for the fifth generation wireless networks. In this study, the authors investigate the performance of a cooperative relaying scheme using NOMA (termed NOMA‐AF‐CRS), where two sources communicate with their corresponding destinations over the same frequency simultaneously through a shared amplify‐and‐forward (AF) relay. First, the closed‐form approximations are derived for the outage probability. The analytical results are further evaluated in the high signal‐to‐noise ratio region to characterise the diversity order achieved by the system. Then, the ergodic sum capacity of NOMA‐AF‐CRS is analysed and an upper bound to the ergodic sum capacity is derived. Finally, simulation results are presented to verify the proposed analysis and demonstrate the advantages of NOMA‐AF‐CRS over the conventional orthogonal multiple access techniques.

In this study, the authors propose a power allocation strategy for full‐duplex relay (FDR) networks, where two cases are considered according to whether the direct link is desired or not. The power allocation is studied in two scenes under the amplify‐and‐forward and decode‐and‐forward protocols, respectively. Aiming at maximising the system capacity, the authors derive the optimal power allocation strategy under the condition that the source and relay have the same maximum power constraint and the total power is limited. The effects of global and individual power constraints for FDR on system capacity are analysed. Simulations verify the theoretical analysis and indicate that the proposed power allocation strategy enhances the system performance greatly compared with uniform power allocation.

Airborne mobile wireless networks (AMWNs), which use spacecrafts and aircrafts such as satellites, airships, airplanes, unmanned aerial vehicles, and other high/medium/low-altitude platforms (HAPs/MAPs/LAPs) can efficiently support high dynamic network topologies and weakly connected communication links. Due to the dramatic dynamics of the AMWNs, it is very difficult to provide the deterministic delay-bounded quality of service (QoS) provisioning for time-sensitive real-time traffics (such as video and audio) over the AMWNs. Alternatively, the statistical delay-bounded QoS provisioning provides an efficient way for guaranteeing delay-bounded QoS requirements for real-time traffics over the AMWNs. On the other hand, because of the diversity of real-time traffics, it is highly demanded to consider the heterogeneity of delay-bounded QoS requirements for distinct real-time services under different HAPs/MAPs/LAPs in the AMWNs. In this paper, we establish the heterogeneous statistical QoS provisioning framework to support the diverse real-time services over the AMWNs. In particular, we formulate the optimization problem to maximize the aggregate effective capacity subject to heterogeneous statistical delay-bounded QoS requirements for both downlink and uplink transmissions-based AMWNs groups (AMWNGs) in the AMWNs. We solve the aggregate effective capacity maximization problems and derive the optimal heterogeneous statistical QoS-driven power allocation schemes for the AMWNs. The numerical analyses we obtained verify that our developed optimal heterogeneous statistical QoS-driven power allocation schemes can significantly increase the aggregate effective capacity for the AMWNs than the other existing schemes.

Power splitting (PS) scheme design is one of the most important challenges in simultaneous wireless information and power transfer-based two-way multiplicative amplify-and-forward relay networks. In this letter, we propose a novel dynamic asymmetric PS (DAPS) scheme to minimize the system outage probability by exploiting the asymmetric instantaneous channel gains between the relay node and the destination nodes. As the formulated optimization problem is a nonconvex problem and difficult to solve, we reformulate it as a fractional programming problem and propose a Dinkelbach-based iterative algorithm to obtain the optimal asymmetric PS ratios. Both the analytical and simulation results demonstrate that the proposed DAPS scheme with the same channel state information overhead can significantly reduce the system outage probability as compared with the existing static symmetric PS scheme.

With a great potential to support multitudinous services and applications, mobile device-to-device (D2D) communications are conceived as a candidate paradigm for the future intelligent transportation systems and mobile Internet. To optimize the performance of underlaying mobile D2D communication systems with mutual interference caused by resource reuse, we propose two scenario-related power allocation schemes and investigate the energy efficiency (EE) and spectral efficiency (SE) trade-off. A 3-D vehicle-to-vehicle channel model is adopted to characterize propagation characteristics in realistic vehicular environments. We observe that a small degradation in EE around its peak value can significantly increase the SE for high vehicular traffic density (VTD) scenarios, while a marginal degradation in SE results in a considerable gain in EE for low VTD scenarios. Therefore, we maximize the SE subject to EE requirement in high VTD scenarios and maximize EE subject to SE requirement in low VTD scenarios. Moreover, to provide comprehensive understanding and further facilitate the practicality of EE-SE trade-off, economic efficiency (ECE) is employed as a general evaluation criterion to assess the efficacy of tradeoff. Finally, extensive simulations are provided to reveal the tradeoff quantitatively and demonstrate the viability that ECE can serve as a general metric for EE–SE trade–off in vehicular environments under different communication conditions.

A new modulation scheme, referred to as space-frequency-mode multi-dimensional hybrid modulation (SFMHM), is proposed to be integrated with multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system in this paper. The key idea of SFMHM is to map a block of information bits to two information carrying units: 1)symbols chosen from a constellation diagram and 2)a subset chosen from all possible combinations of antennas, orbital angular momentum (OAM) modes and subcarriers, which means that only a part of antennas, OAM modes and subcarriers will be activated at any given time. Specifically, the use of the second part will add three additional dimensions to conventional two-dimensional (2-D) amplitude/phase modulation techniques, which will improve the achievable rate significantly. For SFMHM scheme, we propose a computationally efficient mapping method by taking advantage of combinadic representation in combinatorial system, and we further study the achievable rate. Finally, simulation results show that, for the same configuration at the transmitter, SFMHM can achieve higher rate compared with conventional MIMO-OFDM.

In this paper, we develop statistical quality of service (QoS)-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless networks. In particular, first, we analyze the long-term available energy constraints and formulate the EEE maximization problem. Then, we derive the closed-form solutions of optimal power control policies to the EEE maximization problem under the battery capacity dominated constraint, the average harvested energy constraint, and both the battery capacity and average harvested energy constraints, respectively. Furthermore, we derive the threshold to judge whether the optimal power control policy is limited by the battery capacity. The obtained numerical results validate our analyses and show that our developed optimal power control policies can optimize the EEE with statistical QoS provisioning over energy harvesting based wireless networks.

In this paper, we develop the resource allocation scheme with heterogeneous statistical QoS provisioning for wireless powered sensor networks (WPSNs). In particular, we build up the downlink energy transfer and heterogeneous statistical QoS provisioning uplink data transmission models, where the aggregate effective capacity (AEC) is defined as the aggregate throughput under the statistical QoS constraints, for WPSNs. Based on the models, we formulate the AEC maximization problem to jointly optimize the downlink energy assignment and uplink power control scheme. To efficiently solve this problem, we divide it into the hybrid access point determined downlink energy assignment problem and the sensor node determined uplink power control problem, solving which yields the joint downlink energy assignment and uplink power control scheme. Extensive simulations are conducted to evaluate the performance of our proposed heterogeneous QoS-driven resource allocation scheme. The obtained results show that the heterogeneous QoSdriven resource allocation scheme can significantly increase the AEC as compared with the homogeneous QoS-driven resource allocation scheme.

Conventional identification algorithms of space- frequency block codes (SFBC) only utilize the space- domain redundancy between any two receive antennas. In this paper, a novel two-dimensional space-frequency domain redundancy based SFBC identification algorithm for frequency selective fading is proposed in which the detection probability varies with the number of subcarriers. In particular, space-domain redundancy is utilized to construct the cross-correlation function of the estimator while frequency-domain redundancy is incorporated in the hypothesis test statistic. Simulation results verify the viability of the proposed algorithm and its superior performance for short observation periods with comparable computational complexity to the conventional algorithms.

Recently, orbital angular momentum (OAM) based vorticose communication has attracted much attention because of its potential to significantly increase the spectrum efficiency (SE) of wireless communications. However, the multiple radio frequency (RF) chains used for multiple OAM modes lead to an unexpected cost for wireless vorticose communications. To reduce the high cost of RF chains for multiple OAM modes and the high complexity required for signal processing, we first propose the mode modulation (MM) based OAM system to allow multiple OAM modes sharing a common RF chain, which can not only reduce the hardware cost, but also boost the SE by introducing the mode as an additional dimension for data transmission. To solve the problem of how to maximize the SE of MM based OAM systems with the limited RF chains, we develop the equal-probability mode modulation (EMM) scheme, where the OAM modes are selected with equal probability and the signal is transmitted though the activated OAM modes. Moreover, we develop the Huffman coding based adaptive mode modulation (AMM) scheme, which can adaptively choose the OAM modes to further increase the SEs of OAM based vorticose communications. We also develop the OAM- water-filling power allocation policies for both EMM and AMM schemes to achieve the maximum SEs for OAM based vorticose communications. Numerical results are presented to show that the MM can offer the mode dimension for vorticose communications and the AMM scheme can achieve larger SE than the EMM scheme. Also, our developed power allocation policies can further increase the SEs for the MM based OAM communications.

In this paper, we consider a cognitive satellite-terrestrial network where the satellite communication operates in the microwave frequency bands allocated to terrestrial networks in an underlay mode. Taking the statistical delay quality-of-service (QoS) requirements into account, we investigate the effective capacity of the satellite network while satisfying interference-power limitations imposed by terrestrial networks. Specifically, the primary terrestrial transmitters that would result in aggregate interference at the satellite receiver are modeled as points of a Poisson point process (PPP). By characterizing the aggregate interference as a gamma distribution, we obtain a closed-form expression for the effective capacity of the secondary satellite network. Finally, simulation results are provided to not only demonstrate the validity of the theoretical results, but also show the effects of system parameters such as delay exponent of satellite communications, interference-power limitations of terrestrial networks, and intensity of terrestrial transmitters on the performance of the satellite network.

In the non-time-slotted cognitive radio networks (CRNs), the synchronization between PUs and secondary users (SUs) cannot be guaranteed, resulting in two challenging problems: the reactivation-failure of PUs and the frequently unexpected hand-offs among SUs. The reactivation-failure of PUs is the incident that the SUs cannot detect the PUs' reactivation when the SUs are occupying the channels to transmit their data in non-time-slotted CRNs. The frequently unexpected handoffs among SUs are the events that the SU cannot distinguish between the PUs' reactivation and the other SUs' contention, thus causing many unexpected hand-offs among SUs, which severely degrade the achieved throughput of SUs in non-time-slotted CRNs. Employing the energy-detection based wireless full-duplex spectrum sensing schemes, the PUs' reactivation-failure problem can be efficiently solved, thus guaranteeing the required throughput of PUs. However, the key of CRNs is not only the throughput-guarantees for PUs, but also the throughput-boosts for SUs. To optimize the throughput of SUs in multichannel non-time-slotted CRNs, in this paper we develop the pilot-based full-duplex spectrum sensing (PF-SS) scheme and the pilot-based medium access control (P-MAC) protocol to not only guarantee the required throughput of PUs, but also significantly increase the throughput of SUs in multichannel non-time-slotted CRNs. Using the PF-SS scheme, the SUs can identify whether the PUs' signal or the SUs' signal, thus significantly reducing the frequently unexpected hand-offs among SUs. Then, based on the PF-SS scheme, the P-MAC protocol can significantly increase the throughput of SUs. We conduct extensive numerical analyses to show that our developed PF-SS scheme and P-MAC protocol can significantly increase the throughput of SUs while guaranteeing the required throughput for PUs in multichannel non-time-slotted CRNs.

Vehicular Ad-hoc Networks(VANET) has been considered as an important and popular research domain in future Intelligent Transportation Systems(ITS). To support VANET applications, some emerging technologies, such as cloud computing, fog computing, Software Define Network(SDN) are introduced in VANET. Although supported by these technologies, VANET still suffers with some problems, especially reliability issue. Due to the potentially processing nodes(communication links) failure in realistic environment, VANET safety applications, which have strict real time requirement, may fail and cause catastrophic consequence. In this paper, we propose a novel reliability model with delay constraint and fault-tolerant mechanism based on retransmission in hybrid SDN/Fog computing VANET(HSFV) architecture. With the global knowledge of SDN and low delay of fog computing, a novel fault-tolerant reliability optimization particle swarm optimization(FPSO-RO) algorithm is introduced into HSFV architecture. The simulation results indicate that the proposed algorithm could effectively evaluate and improve reliability in real-time VANET systems.

Given the fact that the relay contributes to higher data rate or more reliable transmission at the expense of extra power consumption, we investigate the performance of relay aided Device-to-Device (D2D) communications from the perspective of energy efficiency (EE). Firstly, a closed-form expression for the EE of the considered network over Nakagami-m fading channels is derived. Then, taking into account the effects of practical modulation and coding schemes, we propose a channel quality indicator (CQI) based power control approach to maximize the EE of relay aided D2D communications while guaranteeing the interference limitation. The proposed scheme could avoid unnecessary power increment and is applicable in real time resource allocation. Simulation results demonstrate the validity of the theoretical analysis and illustrate that the CQI based scheme can improve EE.

In this paper, we study the self-interference (SI) cancellation of full-duplex massive MIMO relay systems over Rician fading channels. The decode-and-forward protocol is adopted at the relay station where the channel state information (CSI) is assumed to be imperfect. We demonstrate that the system bottleneck, SI, can be cancelled significantly by zero-forcing (ZF) processing at the relay station which is equipped with massive receive and transmit arrays. We derive a lower bound achievable rate for ZF with statistical CSI. When the number of relay station antennas are large, we illustrate that the performance gap between the achievable rates given by statistical CSI and instantaneous CSI are negligible for different values of Rician K-factors. Since Rayleigh fading is a special case of Rician fading, the results in this paper hold for Rayleigh fading channels.

In this paper, a joint time allocation and power splitting (JTAPS) scheme is considered for the decode- and-forward (DF) energy harvesting (EH) relaying network, where the ``harvest-then-forward" strategy is employed. We focus on designing an optimal JTAPS scheme to conduct the relay under statistical/instantaneous channel state information (CSI) in terms of outage performance. For the statistical CSI, the expressions of the outage probability and outage capacity are derived to determine the optimal power splitting (PS) ratio and time allocation (TA) ratio. For the instantaneous CSI, a joint PS ratio and TA ratio optimization problem is formulated to minimize the outage probability. Considering that the optimization problem is non- convex, a split-step iterative method is proposed to obtain the optimal PS ratio and TA ratio. Finally, simulation results are given to illustrate the advantage of JTAPS scheme with respect to the outage performance.

This paper considers a non-linear energy harvesting (EH) model, better reflecting the properties of practical circuits compared to the linear model, in an amplify-and-forward (AF) relaying network. We focus on the design of relay's power splitting scheme to optimize the system outage performance, and derive the optimal power splitting ratios with both perfect and imperfect channel state information (CSI), respectively. Using the dynamic power splitting scheme, we find that the system outage performance is enhanced in the low signal-to-noise ratio (SNR) regime while converging to an upper bound in the high SNR regime. This finding is significant since it illustrates that the nonlinearity of practical energy harvester brings changes to the design of relaying networks. Simulation results are provided to support our work.

This paper considers a three-step two-way network utilizing an energy harvesting (EH) multiplicative amplify-and-forward (AF) relay. Based on the instantaneous channel state information (CSI), we study a dynamic power splitting (DPS) scheme on how the relay adjusts the power splitting (PS) ratio, achieving a real-time trade-off between the harvested energy and the power of the retransmitted signal. Taking into account a guarantee that both terminals decode the information at the same time, we aim to optimize the worse end-to-end signal-to-noise ratio (SNR) of the two links. As this optimization problem is non-convex and difficult to be solved, an equivalent problem is formulated and an efficient Dinkelbach-based iterative algorithm is proposed to obtain the optimal PS ratio. Simulation results show that the proposed DPS scheme outperforms the exsiting static PS scheme and highlight the effectiveness of the proposed iterative algorithm.

Spectrum sensing based on absolute value cumulating (AVC sensing) has attracted much attention due to its effectiveness in the presence of Laplaican noise and simpleness of implementation. In this paper, we investigate its detection performance and optimal detection threshold. Specifically, based on the derived mean and variance of the test statistic, an accurate expression of the detection probability is given. Using the accurate expression, an optimization problem is formulated to minimize the total error rate of AVC sensing by optimizing the detection threshold with a constraint on false alarm probability, and the optimal detection threshold is derived. Numerical results are provided to support our work.

Automatic modulation classification (AMC) plays a pivotal role for spectrum monitoring in cognitive radio (CR). The objective of this work is to investigate the AMC problem for multiple-input multiple-output (MIMO) systems employing orthogonal frequency division multiplexing (OFDM) under imperfect timing synchronization scenarios. Two major contributions are made in this work: i) specific higher-order cumulants (HOC) are proved to be robust to symbol timing offset (STO). ii) with the feature of multiple HOCs, a random forest based AMC algorithm is proposed for MIMO-OFDM systems, which is robust to timing synchronization error. Numerical simulations are conducted to verify the validation of the algorithm.

This paper presents a novel approach for blind identification of space-frequency block codes. Based on the random matrix theory, we propose principal component sequence as a discriminating feature, which is detected by sliding window in the frequency-domain. With this feature, Euclidean distance is employed for decision making. The proposed algorithm does not need priori knowledge of the signal parameters such as channel coefficients, the modulation mode or noise power. Meanwhile, this algorithm is compatible to identify single-antenna systems and spatial multiplexing of different orders without another module. Moreover, the simulations show the proposed algorithm adapts to multipath fading effectively with a short observation period.

In this study, the authors propose a non‐parametric algorithm to implement the estimation of transmit‐antenna number, which is a prerequisite for blind interception process of multiple‐input multiple‐output orthogonal frequency division multiplexing signals in frequency selective fading. Specifically, a series of test statistics are constructed by exploiting the eigenvalues of the sample covariance matrices from each subcarrier, followed by a combination of these test statistics. As a consequence, the number of transmit antennas can be determined after a serial binary hypothesis testing. The theoretical analysis and simulation results verify the rapid convergence and high reliability of the proposed algorithm at a relatively low signal‐to‐noise ratio.

In this study, the authors investigate the bidirectional wireless information and power transfer (BWIPT) in decode‐and‐forward (DF) relay systems, where the bidirectional relay can decode and forward information from the user to the access point (AP), and assist the wireless power transfer from the AP to the user. The relay employs the power splitting (PS) protocol to coordinate the received signal energy for information transmission and energy harvesting. By converting the multi‐relay system information rate maximisation problem into a convex optimisation problem, the distributed power allocation scheme is obtained to maximise the information rate. Particularly, for single‐relay systems, the authors derive the closed‐form expression of the optimal PS factor, which can maximise the information rate. Simulation results show that the BWIPT for DF relay systems outperforms the BWIPT for amplify‐and‐forward relay systems.

This paper proposes a novel joint resource allocation algorithm combining dynamic user grouping, multi-cell cooperation, and resource block (RB) allocation for single carrier-frequency division multiple access uplink in multi-cell virtual MIMO systems. We first develop the dynamic multi-cell user grouping criteria using minimum mean square error equalization and adaptive modulation with bit error rate (BER) constraint. Then, we formulate and solve a new throughput maximization problem whose resource allocation includes cell selection, dynamic user grouping, and RB pattern assignment. Furthermore, to reduce the computational complexity significantly, especially in the case of large numbers of users and RBs, we present an efficient iterative Hungarian algorithm based on user and resource partitions to solve the problem by decomposing the large scale problem into a series of small scale sub-problems, which can obtain close-to-optimal solution with much lower complexity. The simulation results show that our proposed joint resource allocation algorithm with dynamic multi-cell user grouping scheme achieves better system throughput with BER guarantee than fixed user grouping algorithm and other proposed schemes in the literature.

Optimal relay selection is investigated for secure cooperative communications against an adaptive eavesdropper that can perform eavesdropping if the eavesdropping link has good channel quality or perform jamming otherwise. A number of decode-and-forward relays are available for legitimate communications, among which one relay can be selected to help. For legitimate communications, three cases for availability of the eavesdropping channel information are considered: full channel knowledge, partial channel knowledge, and statistical channel knowledge. An optimal relay selection scheme is proposed for each case. For the first and third cases, exact secrecy outage probability expressions in closed form are derived, and for the second case, an approximate secrecy outage probability is derived, which is tight in the high main-to-eavesdropper ratio regime. Moreover, secrecy diversity order for the proposed relay selection scheme in each case is also derived, which is shown to be a full secrecy diversity. Finally, numerical results are given to verify the theoretical analysis derived in this paper.

The newly imposed heterogeneous statistical delay- bounded quality of service (QoS) provisioning, which refers to the different/variable delay-bounded QoS guarantees among different wireless links, for the fifth-generation (5G) mobile multimedia wireless networks has received much research attention recently. The heterogeneous statistical delay- bounded QoS provisioning can be classified into two categories: centralized and decentralized heterogeneous statistical delay-bounded QoS provisioning where the delay-bounded QoS requirements are centralized at the base station (BS) and distributed at different mobile user equipments (UEs), respectively. The decentralized heterogeneous statistical delay-bounded QoS provisioning is more challenging than the centralized heterogeneous statistical delay-bounded QoS provisioning. In this paper, we build up the system model for decentralized heterogeneous statistical delay-bounded QoS provisioning in terms of aggregate effective capacity and heterogeneous QoS exponents. Based on this model, we develop the optimal joint bandwidth and power allocations scheme to maximize the aggregate effective capacity of uplink transmissions supporting the heterogeneous statistical delay-bounded QoS provisionings over 5G mobile multimedia wireless networks. The BS allocates the bandwidth based on the QoS exponents of all uplinks while the mobile UEs dynamically allocate the power based on the corresponding instantaneous channel state information (CSI), the corresponding QoS exponent, and the bandwidth allocated by the BS. We conduct the extensive simulations to validate and evaluate our developed optimal joint bandwidth and power allocations schemes, showing that our proposed heterogeneous statistical delay-bounded QoS provisioning scheme can significantly increase the aggregate effective capacity as compared with the homogeneous statistical delay-bounded QoS provisioning schemes.

In this paper, we investigate the performance of a distributed space-time coding based hybrid satellite- terrestrial cooperative network (DSTC-HSTCN), where both the satelliterelay and satellite-destination links undergo the Shadowed-Rician fading, whereas the relay-destination link follows the Rayleigh fading. In particular, we address the problem in a downlink distributed Alamouti coded satellite system with a single fixed terrestrial relay. By assuming that amplify-and-forward (AF) protocol is adopted at the terrestrial relay, we first derive the analytical expressions for the joint probability density function (PDF) and moment generating function (MGF) of the signal to noise ratio (SNR) for the cooperatively encoding phase. Then, based on the Meijer-G functions, we present an approximated yet accurate method to evaluate the outage probability and symbol error rate (SER) of the considered networks. Finally, Simulation results are provided to demonstrate the validity of the theoretical analysis.

In multiple‐input–multiple‐output broadcast channels, lattice reduction (LR) preprocessing technique can significantly improve the precoding performance. Among the existing LR algorithms, the fixed complexity Lenstra–Lenstra–Lovasz (fcLLL) algorithm applying limited number of LLL loops is suitable for the real‐time communication system. However, fcLLL algorithm suffers from higher average complexity. Aiming at this problem, a computationally efficient fcLLL (CE‐fcLLL) algorithm for LR‐aided (LRA) precoding is developed in this study. First, the authors analyse the impact of fcLLL algorithm on the signal‐to‐noise ratio performance of LRA precoding by a power factor (PF) which is defined to measure the relation of reduced basis and transmit power of LRA precoding. Then, they propose a CE‐fcLLL algorithm by designing a new LLL loop and introducing new early termination conditions to reduce redundant and inefficient LR operation in fcLLL algorithm. Finally, they define a PF loss factor to optimise the PF threshold and the number of LLL loops, which can lead to a performance‐complexity tradeoff. Simulation results show that the proposed algorithm for LRA precoding can achieve better bit‐error‐rate performance than the fcLLL algorithm with remarkable complexity savings in the same upper complexity bound.

By enabling two adjacent mobile devices to establish a direct link, device-to-device (D2D) communication can increase the system throughput over underlaying wireless networks, where D2D and cellular communications coexist to share the same radio resource. Traditional D2D schemes mainly focus on maximizing the system throughput without taking into account the quality-of-service (QoS) provisioning. To overcome this problem, we develop a framework to investigate the impact of delay-QoS requirement on the performance of D2D and cellular communications in underlaying wireless networks. Then, we propose the optimal power allocation schemes with statistical QoS provisioning for the following two channel modes: 1). co-channel mode based underlaying wireless networks where D2D devices and cellular devices share the same frequency-time resource; 2). orthogonal-channel mode based underlaying wireless networks where the frequency-time resource is partitioned into two parts for D2D devices and cellular devices, respectively. Applying our proposed optimal power allocations into D2D based underlaying wireless networks, we obtain the maximum network throughput subject to a given delay-QoS constraint for above-mentioned two underlaying wireless network modes, respectively. Also conducted is a set of numerical and simulation results to evaluate our proposed QoS-driven power allocation schemes under different delay-QoS requirements.

Since the Information and Communications Technologies (ICT) were designed without taking the energy-saving into account, the unexpected excessive energy consumption of the fourth-generation (4G) and pre-4G wireless networks causes serious carbon dioxide emissions. To achieve green wireless networks, the fifth-generation (5G) wireless networks are expected to significantly increase the network energy efficiency while guaranteeing the quality of service (QoS) for time-sensitive multimedia wireless traffics. In this paper, we develop the statistical delay-bounded QoS driven green power allocation schemes to maximize the effective power efficiency (EPE), which is defined as the statistical-QoS-guaranteed throughput (effective capacity) per unit power, over single-input single-output (SISO) and multipleinput multiple-output (MIMO)-channels based 5G mobile wireless networks. For the SISO-channel based 5G wireless networks, our developed QoS-driven green power allocation scheme converges to the despicking water-filling scheme (despicking channel inversion scheme) when the QoS constraint becomes very loose (stringent). We further develop and analyze the statistical-QoS-driven green power allocation scheme to maximize the EPE over the multiplexing-MIMO based 5G mobile wireless networks. The obtained numerical results show that our developed statistical QoS-driven green power allocation schemes can optimize the EPE over 5G mobile wireless networks, thus enabling the effective implementation of green 5G wireless networks.

This paper focuses on the design and performance analysis of single user detectable multiuser systems based upon continuous phase modulation. This problem is formulated as a special application of mismatched receiver theory, where a closed-form expression for achievable Euclidean distance can be derived. This expression inspires the constructions of two classes of spectrally efficient multiuser designs: nonorthogonal and orthogonal designs. They are both confirmed to offer strong robustness against nonlinear hardware impairment in downlink and uplink transmissions, but differ in spectral efficiency, complexity and achievable minimum Euclidean distance. Moreover, the proposed designs are able to reduce the convergence threshold in serially concatenated multiuser systems. As a general approach to constructing orthogonal and near-orthogonal signals, the proposed techniques find potential applications in multiantenna systems, and full-duplex communications. Compared with existing continuous phase modulated multiuser designs, the proposed techniques offer improved spectral efficiency and significantly reduced detection complexity.

The fifth-generation (5G) communications and wireless networks, which are expected as the next new era of wireless networks, have received much research attention in recent years. The academic and industrial researchers have developed a great deal of 5G candidate techniques to improve the performance of 5G wireless networks, where the most important two metrics are the spectrum efficiency and the quality-of-service (QoS). Jointly using full-duplex (FD) wireless communications and device- to-device (D2D) communications, forming the FD-D2D communications, can significantly increase the spectrum efficiency of 5G wireless networks in frequency/time/space-domains. On the other hand, not only increasing the spectrum efficiency, but also supporting QoS guarantees is very important for 5G wireless networks. However, supporting QoS guarantees for FD-D2D communications imposes the new challenges that we need to provide heterogeneous QoS guarantees for different types of traffics over the same link simultaneously. To overcome the aforementioned problems, in this paper we propose the heterogeneous statistical QoS provisioning framework for FD-D2D communications over 5G wireless networks. In particular, we formulate the optimization problems to maximize the system throughput subject to heterogeneous statistical delay-bound QoS requirements. Then, we convert the resulted non- convex optimization problem into an equivalent convex optimization problem, solving which we can derive the optimal heterogeneous-QoS-driven power allocation scheme to maximize the system throughput while guaranteeing the heterogeneous statistical delay-bound QoS requirements. The extensive simulation results obtained show that our proposed heterogeneous-QoS-driven power allocation scheme can significantly increase the system throughput while guaranteeing heterogeneous statistical delay-bound QoS requirements.

In this paper, we consider two-way full-duplex (FD) relay networks, which allow relaying communications in both directions at the same time and over the same frequency band. We propose a distributed space-time coding scheme, which we call SC-DSTC (Self-Coded Distributed Space-Time Coding), where the main idea is to perform convolutional encoding at the relay node and form a distributed linear convolutional space-time code (DLC-STC) together with the direct link. The convolutional code at the relay is realized by using part of the residual loop interference (RLI), which produces an automatic convolutional encoder. The amplifying factor is optimized when the loop channel information is imperfect. Simulation results show that the proposed SC-DSTC scheme can achieve asynchronous full cooperative diversity and is robust to the error of the loop channel information.

Recently, both academia and industry are moving their research attention to the fifth-generation (5G) wireless networks - the next new era of wireless networks. The wireless full-duplex transmission, as one of promising candidate techniques for 5G, can significantly boost the spectrum efficiency of the wireless networks, thus providing a powerful thrust to optimize the quality-of-service (QoS) performances for the wireless networks. However, due to the heterogeneity caused by different types of simultaneous traffics over the wireless full-duplex link, supporting QoS guarantees for wireless full-duplex networks imposes the new challenges that we need to provide heterogeneous QoS guarantees for different types of traffics over the same link simultaneously. To overcome the aforementioned problems, in this paper we propose the heterogeneous statistical QoS provisioning framework for bidirectional transmission based wireless full-duplex networks. In particular, we formulate the optimization problems to maximize the system throughput subject to heterogeneous statistical delay-bound QoS requirements. Then, we convert the resulted non-convex optimization problem into an equivalent convex optimization problem, solving which we can derive the optimal QoS-driven power allocation scheme to maximize the system throughput while guaranteeing the heterogeneous statistical delay-bound QoS requirements. The extensive simulation results obtained show that our proposed QoS-driven power allocation scheme for heterogeneous statistical delay-bound QoS requirements can achieve larger aggregate system throughput than the scheme for the homogeneous statistical delay-bound QoS requirement over 5G mobile wireless full-duplex networks.

Eigen-beamforming is an optimal beamforming scheme for full-dimension multi-input multi-output (FD-MIMO). However, it suffers from high complexity of the singular value decomposition (SVD) of the 3D channel matrix. In this paper, we propose a low complexity dual layer beamforming scheme to exploit both the horizontal and vertical degrees of freedom. The proposed scheme first segments the channel matrix into several sub-channel matrices. Then, by selecting the vertical and horizontal beamforming from the sub-channel matrices respectively, the proposed scheme can reduce the complexity, while achieving the performance approximate to the optimal eigen-beamforming scheme. Moreover, to enable practical implementation, a hybrid codebook design is proposed which exploits the structure of the dual layer beamforming to reduce feedback overhead. According to the different correlation characteristics in horizontal and vertical direction, we design different codebooks for the horizontal and vertical beamforming. Simulation results demonstrate that the proposed scheme can effectively improve the spectral efficiency of FD-MIMO systems with limited feedback, especially for the cell edge users.

In this paper, the performance of a distributed Space-Time coded hybrid satellite-terrestrial cooperative network (DSTC-HSTCN) is investigated. In particular, we address the problem in a downlink distributed Alamouti coded satellite system with a single fixed terrestrial relay adopting amplify-and- forward protocol. By modeling the satellite- relay/destination and relay-destination links as Shadowed-Rician and Rayleigh distributions, respectively, we derive a closed-form expression for average symbol error rate (SER) with quadrature phase shift keying modulation. Simulation results verify the validity of the theoretical analysis and show the performance improvement of the hybrid satellite- terrestrial cooperative network (HSTCN).

For the deep-space communications, the long distance transmission significantly deteriorates the received signal-to-noise ratio (SNR) at the receiver. Also, the accelerating movement between the high-speed transmitter-receiver pair causes the accelerating Doppler-shift. To address the Doppler-shift acquisition problem under not only the very low SNR but also the very high accelerating movement scenarios, in this paper, we develop one joint-detection (JD) scheme including two algorithms, called the single JD and the iterative JD, respectively, to significantly increase the acquisition probability. First, the single JD algorithm, which has a concise closed-form expression for the net increment of acquisition probability, uses multiple combination periods to narrow the search range for the next acquisition. Second, the iterative JD algorithm, which builds on the iterative of single JD algorithm, achieves the further increase of acquisition probability. Moreover, the simulation results show that our proposed scheme can significantly increase the acquisition probability of Doppler-shift for the deep-space communications.

Because of the asynchronization between primary and secondary wireless networks, the synchronization between primary users (PUs) and secondary users (SUs) can be hardly guaranteed in nontime-slotted cognitive radio networks (CRNs). In this paper, we propose a novel framework for multichannel nontime-slotted CRNs, where the PUs randomly access and leave the licensed channels. Since the PUs cannot distinguish between primary and secondary signals, the PUs may sense a busy channel when the PUs start to reactivate during the SUs' transmission, thus generating a collision or entering the backoff stage. To guarantee the high-throughput transmission of the PUs and increase the channel utilization of the SUs, in this paper, we propose the wireless full-duplex spectrum sensing (FD-SS) scheme for SUs in multichannel nontime-slotted CRNs. Using our developed FD-SS scheme, the SUs can timely sense the PUs' reactivation during the same time when the SUs are transmitting their signals. Then, based on our proposed wireless FD-SS scheme, we further develop and analyze the wireless full-duplex cognitive medium access control (FDC-MAC) protocol for multichannel nontime-slotted CRNs. We conduct extensive numerical analyses, showing that our developed FD-SS scheme and FDC-MAC protocol can efficiently guarantee the high-throughput transmission of the PUs and increase the channel utilization of the SUs without requiring the synchronization between the PUs and the SUs over the multichannel nontime-slotted CRNs.

To guarantee the real-time transmission for time-sensitive traffic, we need to take delay-bound quality-of-service (QoS) into account when designing the wireless cellular networks. The traditional powerful QoS guarantee technique, called the homogeneous statistical QoS provisioning, assumes that the QoS provisioning of each link can be individually processed. In order to further significantly increase the global system throughput, the available resources of all links need to be jointly controlled, which is typically suitable for downlink transmissions over wireless cellular networks. Under this setup, we need to consider the diverse delay-bound QoS provisionings for different links at the same time, which represents the new heterogeneous statistical QoS provisioning framework and imposes many new challenges not encountered before in wireless networks. To overcome these problems, in this paper we propose the heterogeneous statistical QoS provisioning framework for high-speed downlink transmissions in wireless cellular networks. In particular, we formulate the optimization problem to maximize the downlink throughput subject to heterogeneous statistical delay-bound QoS requirements. For solving this optimization problem, we develop the heterogeneous-QoS-driven power allocation scheme to derive the closed-form solutions which can maximize the global system throughput while guaranteeing the heterogeneous delay-bound QoS for the entire wireless cellular networks. We show that the heterogeneous-QoS-driven power allocation provides more generic framework for downlink transmissions. The extensive simulation results obtained show that our proposed heterogeneous-QoS-driven power allocation scheme can achieve the global optimization of wireless resource efficiency, thus significantly increasing the global system throughput as compared with the homogeneous statistical delay-bound QoS provisioning schemes.

By enabling two mobile devices, which are far away from the base station (BS) and very close to each other, to establish a direct link, device-to-device (D2D) communications can significantly increase the system throughput for wireless cellular networks. Traditional D2D schemes are mainly based on the half-duplex transmission mode. However, the short distance between the two D2D mobile devices can not only increase the received signal-to-noise ratio (SNR) but also increase the signal-to-self-interference-plus-noise ratio (SSINR), which motivates us to apply the wireless full-duplex transmission based D2D communications into wireless cellular networks. To further increase the ergodic capacity of the wireless cellular networks, in the paper we propose the full-duplex D2D communications framework for wireless cellular networks. In particular, we formulate the ergodic capacity optimization problem for full-duplex D2D communications based wireless cellular networks. To solve this optimization problem, we develop the optimal full-duplex power allocation schemes to maximize the ergodic capacity of the wireless cellular networks. Also conducted is a set of numerical and simulation results to evaluate the ergodic capacity gain of our proposed full-duplex power allocation schemes as compared with the traditional half-duplex transmission based D2D communications.

In this paper, an evolutionary game based relay assignment algorithm is proposed for a cooperative network consisting of multiple source users (SUs) and multiple selfish busy relay users (RUs) with their own packets to transmit. Each RU can select either non-cooperative mode (i.e., direct transmission with its own receiver pair) or cooperative mode (i.e., relay transmission for the SUs). Thus, for the relay assignment, there exists an inevitable problem for all RUs: whether to cooperate and whom to cooperate with. Considering all RUs' different individual channel conditions, a variable-population evolutionary game model is formulated to analyze the cooperation possibility and relay competition among all selfish RUs, which is performed in a distributed manner. Moreover, this algorithm is shown to improve the entire network's performance and compared with the centralized optimal relay assignment algorithm.

High peak‐to‐average power ratio (PAPR) is a major drawback of orthogonal frequency division multiplexing (OFDM) systems. A new companding scheme is proposed to reduce PAPR by transforming the statistics of the companded signal into exponential distribution with adjustable parameters. The proposed scheme can enhance the bit error rate (BER) performance significantly by minimising the companding distortion in the reduction of PAPR. Moreover, with the introduction of an inflexion point and transform parameters, the proposed scheme can offer more flexibility in the PAPR reduction, and therefore achieves a better tradeoff among the PAPR reduction, BER and power spectral density (PSD) performance. With a theoretical analysis presented, the parameter selection criteria are derived. Simulation results verify that the proposed scheme can significantly improve the BER and PSD performance while reducing PAPR effectively.

This study analyses the achievable cooperative diversity order of the distributed linear convolutional space‐time coding (DLC‐STC) scheme for time–frequency asynchronous cooperative networks. The authors first prove that perfect time or frequency synchronisation is impractical for cooperative networks with multiple relays serving multiple destinations even when the relays know all accurate time delays and frequency offsets. Then the DLC‐STC scheme, in which the exact time synchronisation at the relay nodes is unnecessary, is introduced into this type of cooperative networks. This study proves that the achievable time–frequency asynchronous cooperative diversity order of the DLC‐STC scheme with maximum‐likelihood receivers is equal to the number of relays. Simulation results verify the analysis.

In this paper, two-relay full-duplex asynchronous cooperative networks with cross-talks are considered. We show that the cross-talk interference at relays cannot be removed well even when the relays know all the accurate channel state information, for which a partial distributed linear convolutional space-time coding scheme (partial DLC-STC) is proposed by using the two-relay cross-talks instead of removing them. Simulation results show that the partial DLC-STC for two-relay full-duplex asynchronous cooperative networks can achieve full asynchronous diversity.

We consider the full-duplex transmission over bidirectional channels with imperfect self-interference cancelation in wireless networks. In particular, together using propagation-domain interference suppression, analog-domain interference cancellation, and digital-domain interference cancellation, we develop the optimal dynamic power allocation schemes for the wireless full-duplex sum-rate optimization problem which aims at maximizing the sum-rate of wireless full-duplex bidirectional transmissions. In the high signal-to-interference-plus-noise ratio (SINR) region, the full-duplex sum-rate maximization problem is a convex optimization problem. For interference-dominated wireless full-duplex transmission in the high SINR region, we derive the closed-form expression for the optimal dynamic power allocation scheme. For non-interference-dominated wireless full-duplex transmission in the high SINR region, we obtain the optimal dynamic power allocation scheme by numerically solving the corresponding Karush-Kuhn-Tucker (KKT) conditions. While the full-duplex sum-rate maximization problem is usually not a convex optimization problem, by developing the tightest lower-bound function and using the logarithmic change of variables technique, we convert the full-duplex sum-rate maximization problem to a convex optimization problem. Then, using our proposed iteration algorithm, we can numerically derive the optimal dynamic power allocation scheme for the more generic scenario. Also presented are the numerical results which validate our developed optimal dynamic power allocation schemes.

This paper deals with time and frequency offset in coordinated multipoint (CoMP) transmission/reception networks by using distributed linear convolutional space-time coding (DLC-STC). We first prove that perfect time synchronization is impractical for CoMP transmission/reception networks. Then the DLC-STC scheme, in which exact time synchronization at the relay nodes is unnecessary, is proposed for the CoMP joint processing mode (CoMP-JP). Finally, we show the detecting method by minimum mean-squared error decision-feedback equalizer (MMSE-DFE) receivers with any frequency offsets. Simulation results show that with MMSE-DFE receivers, the proposed DLC-STC scheme outperforms the delay diversity scheme and the MMSE-DFE receivers can achieve the same diversity orders as the maximum likelihood sequence detection (MLSD) receivers.

In the scenario of dynamic spectrum access application for orthogonal frequency division multiplexing (OFDM)‐based cognitive radio systems, the out‐of‐band radiation of the OFDM signals must be strictly controlled to protect licensed users in the adjacent band. This study proposes a constellation expansion‐based scheme for suppressing the sidelobes. The proposed approach can provide much faster decaying sidelobes by remapping the adjacent symbols in the original sequence with preferred mapping or alternative mapping chosen from a higher constellation set. Moreover, a simple clipping technique, which has little effect on the sidelobe suppression, is used for peak‐to‐average power ratio reduction of the proposed system. At the receiver, the specific associations in the mapping can be used to correct decision errors. Simulation results show that our proposed scheme can effectively reduce sidelobe power levels with only a slight bit error rate performance degradation.

Spectrum and power efficiencies are both crucial to design efficient wireless networks. In past two decades, spectrum and power efficiencies of wireless networks are optimized separately. However, to increase the spectrum efficiency while reducing the energy consumption, it is necessary to jointly optimize spectrum and power efficiencies of wireless networks. Supporting the statistical quality of service (QoS) provisionings for real-time traffic is crucial, but imposes new challenges, in the next generation wireless networks. In this paper, we propose an efficient framework to jointly optimize effective spectrum efficiency (ESE) and effective power efficiency (EPE) under different statistical QoS guarantees constraints to support the real-time traffic over wireless networks. In particular, we derive the relationship between ESE and EPE under statistical QoS provisioning constraint. Based on this relationship, we obtain the mutually beneficial (MB) region and the contention-based (CB) region. In the MB region, we propose a novel strategy to achieve the joint effective spectrum and power efficiencies optimization using the average transmit power control. In the CB region, we propose the wireless-relay-based strategy to jointly optimize the effective capacity and power efficiency. In both MB and CB regions, we develop the dynamic transmit-power control strategy and the MIMO-based strategy to jointly maximize the effective spectrum and power efficiencies. Also conducted is a set of numerical evaluations showing that our proposed strategies can achieve superior joint spectrum and power efficiencies optimization for the diverse statistical QoS provisionings.

To enable multiple mobile users to transmit their signals simultaneously over the same sub-channels, the virtual multiple-input multiple-output (V-MIMO) techniques can exploit the multiple-input multiple-output (MIMO) spectrum efficiency gain. Traditional V-MIMO transmission schemes mainly focus on maximizing the throughput of grouped mobile users without taking into account the quality-of-service (QoS) provisionings. In this paper, we propose the optimal power allocation schemes with statistical QoS provisionings to maximize the effective capacity of non-collaborative/collaborative V-MIMO wireless networks, respectively. For non-collaborative V-MIMO wireless networks, the mobile users in one V-MIMO group transmit signals independently over the same sub-channels. In the view point of existing mobile users, they solely occupy the sub-channels. Thus, the existing mobile users employ the QoS-driven single-user power allocation scheme to maximize their effective capacity. By converting the non-collaborative V-MIMO transmission optimization problem into a strictly convex optimization problem, we derive the QoS-driven power allocation scheme for the newly added mobile users to maximize their effective capacity. For collaborative V-MIMO wireless networks where the mobile users in one group can collaboratively transmit their signals, we derive the QoS-driven collaborative power allocation schemes for both the existing and the newly added mobile users. Also conducted is a set of simulation evaluations, showing that our proposed power allocation schemes for V-MIMO wireless networks outperform the other existing schemes.

Manifold learning concerns the local manifold structure of high dimensional data, and many related algorithms are developed to improve image classification performance. None of them, however, consider both the relationships among pixels in images and the geometrical properties of various images during learning the reduced space. In this paper, we propose a linear approach, called two-dimensional maximum local variation (2DMLV), for face recognition. In 2DMLV, we encode the relationships among pixels in images using the image Euclidean distance instead of conventional Euclidean distance in estimating the variation of values of images, and then incorporate the local variation, which characterizes the diversity of images and discriminating information, into the objective function of dimensionality reduction. Extensive experiments demonstrate the effectiveness of our approach.

In this paper, a two-relay full-duplex asynchronous cooperative network with the amplify-and-forward (AF) protocol is considered. We propose two distributed space-time coding schemes for the cases with and without cross-talks, respectively. In the first case, each relay can receive the signal sent by the other through the cross-talk link. We first study the feasibility of cross-talk cancellation in this network and show that the cross-talk interference cannot be removed well. For this reason, we design space-time codes by utilizing the cross-talk signals instead of removing them. In the other case, the self-coding is realized individually through the loop channel at each relay node and the signals from the two relay nodes form a space-time code. The achievable cooperative diversity of both cases is investigated and the conditions to achieve full cooperative diversity are presented. Simulation results verify the theoretical analysis.

Spectrum and power efficiencies are both crucial to design efficient wireless networks. In past two decades, spectrum and power efficiencies of wireless networks are optimized separately. However, to increase the spectrum efficiency and reduce the energy consumption, it is necessary to jointly optimize spectrum and power efficiencies of wireless networks. In this paper, we propose an efficient framework to model the statistical delay quality of service (QoS) guarantees, in terms of QoS exponent, effective spectrum efficiency (ESE), and effective power efficiency (EPE), for joint spectrum and power efficiencies optimization to transmit real-time traffics over wireless networks. In particular, we derive the relationship between ESE and EPE under statistical QoS provisioning constraint. Based on the relationship, we obtain the mutually beneficial region and contention-based region. We also analyze the global maximum EPE and optimal average transmit power under various statistical QoS guarantees. Then, we develop a novel strategy to achieve the joint spectrum and power efficiencies optimization. Also conducted is a set of numerical evaluations showing that our proposed strategy can achieve superior joint spectrum and power efficiencies optimization for various statistical QoS provisionings.

We propose the quality-of-service (QoS) driven power allocation scheme for wireless links under average and peak power constraints. By integrating information theory with the principle of effective capacity, our proposed scheme aims at maximizing the system throughput subject to a given delay-QoS constraint. Over the block fading channel, we derive the optimal power allocation scheme to maximize the effective capacity. The analyses and numerical results show that our optimal power allocation scheme converges to the despicking water-filling scheme when the QoS constraint becomes very loose. On the other hand, our optimal power allocation scheme reduces to the dispicking channel inversion scheme when the QoS constraint gets very stringent. Two non-optimal power allocation schemes are described for comparison purposes. We also propose and evaluate the independent optimization for the multicarrier system.

We propose the quality-of-service (QoS) driven power allocation scheme for full-duplex wireless links. By integrating information theory with the principle of effective capacity, we build two models - local transmit power related self-interference (LTPRS) model and local transmit power unrelated self-interference (LTPUS) model to analyze the full-duplex transmission, respectively. In the LTPRS model, self-interference directly corresponds to the level of local transmit power. In the LTPUS model, self-interference does not directly relate to the level of local transmit power. For both of these two models, we derive the optimal power allocation schemes, which aim at maximizing the system throughput subject to a given delay QoS constraint, over bidirectional wireless links with full-duplex transmission. The analyses and numerical results verify that our proposed power allocation scheme can efficiently support diverse QoS requirement over full-duplex wireless links. For LTPRS model, the optimal power allocation scheme converges to a constant power scheme when the QoS constraint gets very loose and the optimal power allocation scheme reduces to the channel inversion scheme when the QoS constraint becomes very stringent. For LTPUS model, the optimal power allocation scheme converges to the the water-filling scheme when the QoS constraint gets very loose and the optimal power allocation scheme reduces to the channel inversion scheme when the QoS constraint becomes very stringent.

Integrating information theory with the principle of effective capacity, we propose the optimal resource allocation schemes for wireless full duplex and half duplex relay networks, respectively, to support the statistical quality-of-service (QoS) provisioning. In particular, we introduce a new control parameter, termed cancellation coefficient, to characterize the performance of full duplex relay transmission mode. For both amplitude-and-forward (AF) and decode-and-forward (DF) relay networks, we develop the dynamic hybrid resource allocation policies under full duplex and half duplex transmission modes to maximize the network throughput for the given delay QoS constraint measured by the QoS exponent. The numerical results obtained verify that our proposed resource allocation schemes can support diverse QoS requirements over wireless relay networks under full duplex and half duplex transmission modes. Our analysis indicates that the optimal effective capacity of perfect full duplex transmission mode is not the just twice as much as the optimal effective capacity of half duplex transmission mode. Our numerical analyses also show that the hybrid transmission mode can achieve better performance than just using full duplex or half duplex transmission mode alone.

In order to provide an increased capacity for voice users in emergency scenarios, a low-medium-altitude aerial platform based time-division-duplex long term evolution (TD-LTE) system referred to as Aerial LTE, is presented in this paper. Furthermore, a novel radio resource allocation mechanism is proposed for both the Aerial LTE downlink and uplink, which is modeled as a cooperative game to provide real-time voice communications with as many users as possible. Our simulation results demonstrate that compared with the traditional radio resource management algorithms, the proposed algorithm achieves the largest capacity, i.e., the number of serviced users.

In order to provide an increased capacity, throughput and QoS guarantee for terrestrial users in emergency scenarios, a low-medium-altitude aerial platform based time-division-duplex long term evolution (TD-LTE) system referred to as Aerial LTE, is presented in this paper. Additionally a power-efficient radio resource allocation mechanism is proposed for both the Aerial LTE downlink and uplink, which is modeled as a cooperative game. Our simulation results demonstrate that the proposed algorithm imposes an attractive tradeoff between the achievable throughput and the power consumption while ensuring fairness among users.

Using only one training symbol, a novel cross ambiguity function (CAF) based integer frequency offset (IFO) estimator for OFDM systems is proposed. From the energy distribution characteristics of the ideal CAF, an energy-detection based metric is obtained. By designing a training symbol whose ambiguity function (AF) is a valid approximation of the ideal thumbtack-type AF, a high-accuracy and full-range IFO estimation can be achieved over frequency-selective fading channels. Furthermore, the adoption of the CAF expression in terms of time-domain signals keeps the complexity of the proposed algorithm at a relatively low level. Simulation results verify its superior accuracy of the IFO estimation over conventional algorithms.

In this paper, we propose two distributed linear convolutional space-time coding (DLC-STC) schemes for full-duplex (FD) asynchronous cooperative communications. The DLC-STC Scheme 1 is for the case of the complete loop channel cancellation, which achieves the full asynchronous cooperative diversity. The DLC-STC Scheme 2 is for the case of the partial loop channel cancellation and amplifying, where some loop signals are used as the self-coding instead of treated as interference to be directly cancelled. We show this scheme can achieve full asynchronous cooperative diversity. We then evaluate the performance of the two schemes when loop channel information is not accurate and present an amplifying factor control method for the DLC-STC Scheme 2 to improve its performance with inaccurate loop channel information. Simulation results show that the DLC-STC Scheme 1 outperforms the DLC-STC Scheme 2 and the delay diversity scheme if perfect or high quality loop channel information is available at the relay, while the DLC-STC Scheme 2 achieves better performance if the loop channel information is imperfect.

Abstract In the IEEE 802.11 wireless LAN (WLAN), the fundamental medium access control (MAC) mechanism—distributed coordination function (DCF), only supports best‐effort service, and is unaware of the quality‐of‐service (QoS). IEEE 802.11e enhanced distributed channel access (EDCA) supports service differentiation by differentiating contention parameters. This may introduce the problem of non‐cooperative service differentiation. Hence, an incompletely cooperative EDCA (IC‐EDCA) is proposed in this paper to solve the problem. In IC‐EDCA, each node that is cooperative a priori adjusts its contention parameters (e.g., the contention window (CW)) adaptively to the estimated system state (e.g., the number of competing nodes of each service priority). To implement IC‐EDCA in current WLAN nodes, a frame‐analytic estimation algorithm is presented. Moreover, an analytical model is proposed to analyze the performance of IC‐EDCA under saturation cases. Extensive simulations are also carried out to compare the performances of DCF, EDCA, incompletely cooperative game, and IC‐EDCA, and to evaluate the accuracy of the proposed performance model. The simulation results show that IC‐EDCA performs better than DCF, EDCA, and incompletely cooperative game in terms of system throughput or QoS, and that the proposed analytical model is valid. Copyright © 2010 John Wiley & Sons, Ltd.

In this paper, we evaluate the impact of a mix of co-channel MIMO interferers on the performance of Alamouti Coding in the downlink of a cellular-like system. In particular, taking into account the effects of both path-loss and Rayleigh fading, we derive closed-form expressions for the probability density functions of the resulting signal-to-interference ratios. Simulation results verify the validity of the analyses.

To lessen the environmental impact of the communication industry, Green Communications has achieved increasing attention from government, academia, and industry. However, how to define a green communication system has been an open topic. In this paper, we carry out a comprehensive analysis of the b/s/Hz bandwidth efficiency, the b/s/Hz/m2area spectral efficiency, the b/TENU power efficiency, the b/s/Hz/W power efficiency, and the (b-m)/s/Hz/W green efficiency of a wireless link. After comparing the performance of the green efficiency with the other efficiencies, we present an adaptive modulation and coding scheme to approach the maximum green efficiency, which provides an effective way to Green Communications.

Abstract In this paper, we consider the problem of stimulating cooperation and resource allocation in cooperative transmission networks. We formulate this problem as a sellers' market competition where a relay is willing to share its resource with multiple users. We use a Stackelberg game to jointly consider the benefits of the relay and the users. Firstly, the relay determines the price of relaying according to the user demand. Secondly, the users purchase the optimal amount of resources to maximize their utilities. Although the Nash equilibrium, i.e., the solution of the game, can be obtained in a centralized manner, we develop a distributed algorithm to search the Nash equilibrium, which is more applicable in practical systems. Also, the convergence conditions of the algorithm are analyzed. Simulation results show, by using the distributed algorithm, the relay and the users could determine what price should ask for and how much bandwidth should buy, respectively. Copyright © 2010 John Wiley & Sons, Ltd.

Recently, a new concept "Green Radio" has been focused, which means to reduce the existing energy consumption of information and communication technologies (ICTs). Cellular networks account for a rather large share of energy use, lowering their energy consumption appears beneficial, especially BS, which costs the most energy in the cell. Macro-femto network, as a new two-tier cellular network, has obvious advantages in lowering cellular energy consumption. In this paper, we firstly introduce a spatial two-tier model and two new metrics for analyzing the cellular network. Secondly, we analyze the downlink energy consumption of BSs and femtocell access points (FAPs). Thirdly, we provide a novel energy efficient spectrum allocation strategy in marco-femto cellular networks for minimal downlink energy consumption. Finally, simulation results show that this new spectrum allocation strategy can help the cellular network to be energy efficient.

In this paper, the impact of co-channel MIMO interference on MIMO Beamforming (MBF) in the desired link is investigated. The exact closed-form expression of the probability density function (pdf ) of the signal-to-interference ratio when the desired user has one antenna is derived. Due to the unavailability of the closed-form pdf expression for arbitrary (N,M) (where N and M are the number of transmit and receive antennas, respectively), a simple approximation for an arbitrary number of antennas is proposed and used to analyze the impact of various MIMO modes used by the co-channel base stations. Simulation results verify the validity of the analysis and the impact of cochannel MIMO modes on the desired MBF receiver is discussed.

Rate adaptation algorithms play a crucial role in IEEE 802.11 WLANs. While the network performance depends greatly on the rate adaptation algorithms, the detailed implementation is left to vendors. Due to its simplicity and practicality, threshold-based rate adaptation algorithms are widely adopted in commercial IEEE 802.11 devices. Taking the popular ARF algorithm for example, the data rate is increased when ten consecutive transmissions are successful and a date rate downshift is triggered by two consecutive failed transmissions. Although widely deployed, the optimal selection of the up/down thresholds for the rate adaptation algorithms remains an open problem. In this paper, we first investigate the threshold-based rate adaptation algorithm via a reverse engineering approach where the implicit objective function is revealed. Next, we propose a threshold optimization algorithm which can dynamically adjust the up/down thresholds and converge to the stochastic optimum solution in arbitrary stationary random channel environment. The performance enhancement by tuning the thresholds optimally is validated by simulations.

Rate adaptation algorithms play a crucial role in IEEE 802.11 WLANs. While the network performance depends greatly on the rate adaptation algorithms, the detailed implementation is left to vendors. Due to its simplicity and practicality, the generic rate adaptation algorithm based on up/down thresholds is widely adopted in commercial IEEE 802.11 devices. Taking the popular ARF algorithm for example, the data rate is increased when ten consecutive transmissions are successful and a date rate downshift is triggered by two consecutive failed transmissions. Although widely deployed, disclosing the implicit objective function that the rate adaptation algorithm is dynamically maximizing, remains as an open problem in the literature. In this paper, we investigate the thresholds-based rate adaptation algorithm via a reverse engineering perspective where the implicit objective function is revealed. We consider this reverse engineering study of the thresholds-based rate adaptation algorithm as an important first step towards a comprehensive understanding on the rate adaptation mechanism designs and the complex interactions among multiple IEEE 802.11 stations.

The transmit adaptation is a key technique to realize the full potentials of orthogonal frequency-division multiplexing (OFDM) systems. In this paper, we first present a new channel state information (CSI) model in order to save the reverse channel spectrum. By using clustering and interpolation according to the correlation between subcarriers, the estimation of CSI is obtained at the transmitter. Then, the transmit adaptation scheme including power allocation and adaptive modulation is proposed. In this scheme, the transmit power is allocated to the subcarriers by water filling theory, during which a fast search algorithm for the water filling line is presented, and then the adaptive modulation is carried out maintaining a certain system BER. Compared with the existing schemes, the proposed scheme achieves a better performance with the same cost of feedback data.

In the traditional medium access control (MAC) protocols for wireless sensor networks (WSNs), energy consumption is traded for throughput and delay. However, in future WSNs, throughput and delay performance had better not be sacrificed for energy conservation. Here first, an incompletely cooperative game-theoretic heuristic-based constraint optimisation framework is introduced to achieve the goals of throughput, delay and energy conservation simultaneously. Then a simplified game-theoretic MAC (G-MAC) protocol is presented, which can be easily implemented in WSNs. Simulation results show that compared with two typical MAC protocols for WSNs, sensor MAC and timeout MAC, G-MAC can increase system throughput, and decrease delay and packet-loss-rate, while maintaining relatively low energy consumption.

In this paper, we propose for multi-rate ad hoc networks a cross-layer design using power control, called MRPC. MRPC consists of two parts. First, we propose a multi-rate power controlled MAC protocol, called MRPC-MAC. By carefully controlling the transmission power, it can enable concurrent transmissions, which is otherwise impossible for the IEEE 802.11 standard. Second, we propose a multi-rate power controlled routing protocol, called MRPC-Routing. Different from traditional routing protocols, MRPC-Routing is not intended to find end-to-end paths, rather, it determines the next hop right before transmitting packets at the MAC layer. In this protocol, it uses the effective transport capacity as the routing metric such that short links with high bandwidth are preferred and more concurrent transmissions can be enabled. Having these coupled power controlled MAC protocol and routing protocol, MRPC can greatly improve the spatial reuse and the network throughput. Simulation results also show MRPC-MAC, MRPC-routing, and especially MRPC, can improve the network throughput significantly.

Abstract IEEE 802.11 is one of the most influential wireless LAN (WLAN) standards. Point coordination function (PCF) is its medium access control (MAC) protocol with real‐time traffic (rt‐traffic) quality‐of‐service (QoS) guarantees. In PCF, it is very likely that non‐real‐time traffic (nrt‐traffic) will use the contention free period (CFP) that should be dedicated to traffic having higher priority such as rt‐traffic. Therefore, a modified PCF protocol called MPCF, which is based on hub polling and an integrated QoS differentiation, is presented in this paper. With the integrated QoS differentiation, MPCF can prioritize bandwidth requests according to service classes and QoS requirements. With hub polling, MPCF can reduce the bandwidth for control frames and improve the network throughput. A simple and accurate analytical model is derived and presented in this paper to calculate the system throughput of MPCF. Simulation results show that MPCF protocol is much better than PCF in terms of system capacity and rt‐traffic QoS guarantees. Copyright © 2008 John Wiley & Sons, Ltd.

Game theory is a useful and powerful tool for performance analysis and optimization of wireless mesh networks (WMNs). Based on incompletely cooperative game theory, a mesh router can estimate the game state (e.g., the number of competing nodes), and broadcast this information to its clients. Then all the clients play a cooperative game based on the estimated game state, and achieve the optimal equilibrium strategy. For each client to implement the game independently as it cannot get the game state accurately or timely sometimes, particle swarm optimization is introduced into the game, and a game-theoretic particle swarm optimization scheme (G-PSO) for WMNs is presented in this paper. Simulation results show that G-PSO can increase system throughput and decrease delay, jitter and packet-loss-rate.

In IEEE 802.11 WLANs, the fundamental MAC mechanism - DCF, only supports best-effort service, and is unaware of QoS. IEEE 802.11e EDCA supports service differentiation by differentiating contention parameters. This may introduce the problem of selfish traffics with rational nodes. Hence, game-theoretic EDCA (G-EDCA) is proposed in this paper to solve the problem. Moreover, a simple and run-time estimation mechanism is presented to implement G-EDCA in current WLANs. Extensive simulations are also carried out to compare the performances of DCF, EDCA and G-EDCA. The simulation results show that G-EDCA performs better than DCF and EDCA in terms of system throughput and QoS.

In WSNs, energy conservation is the primary goal, while throughput and delay are less important. So used energy is traded for throughput and delay. In this paper, a novel concept of incompletely cooperative game theory is used in WSNs to simultaneously achieve all the goals. In the game, each node adjusts its equilibrium strategy to the estimated game state. After discussing the utility function of the game, the equilibrium strategy for the game in WSNs is presented, Moreover, a simplified game-theoretic MAC protocol (G-MAC) is provided for WSNs, by using an auto degressive backoff mechanism, which is easy to be implemented. Simulation results show that the incompletely cooperative game can increase system throughput, and decrease delay and packet-loss-rate, while still maintaining reasonable energy consumption, and that G-MAC supports the game effectively.

The fundamental medium access control mechanism in IEEE 802.11 wireless LANs (WLANs)–distributed coordination function (DCF) only supports the best-effort service and does not support quality-of-service (QoS) differentiation. Enhanced distributed channel access (EDCA) in IEEE 802.11e supports delay differentiation. A new approach, EDCA+, is proposed to enhance QoS over WLANs. It simultaneously achieves bandwidth, delay and jitter differentiation by distinguishing the minimum contention window, the maximum backoff stage or persistent factor and packet-loss rate differentiation by distinguishing the retry limit. Analytical models are proposed to analyse the performance of EDCA+ in terms of throughput, bandwidth, delay, jitter and packet-loss rate. Extensive simulations are also carried out to evaluate the accuracy of the proposed performance models and to compare the performance of DCF, EDCA and EDCA+. The simulation results show that EDCA+ performs better than DCF and EDCA in ensuring integrated QoS, and that the proposed analytical models are valid.

Recently, game theory becomes a useful and powerful tool to research mobile ad hoc networks (MANETs). Wireless LANs (WLANs) can work under both infrastructure and ad hoc modes, and are the most widely used MANETs. In this paper, we propose a novel concept of incompletely cooperative game theory and use it to improve the performance of WLANs. In this game, firstly, each node estimates the current state of the game (i.e., the number of competing nodes) by detecting the channel. Secondly, each node changes its equilibrium strategy by tuning its local contention parameters based on the estimated game state. Finally, the game is repeated finitely to get the optimal performance. Our simulation results show that the incompletely cooperative game can increase system throughput, and decrease delay, jitter and packet-loss-rate.

Directional distributed co-ordination function (D-DCF), a modified medium access control protocol of IEEE 802.11, is proposed to support hybrid antennas such as smart adaptive array antennas and normal omni-directional antennas, in one wireless local area network cell. Nodes equipped with smart antennas follow D-DCF and nodes equipped with normal antennas follow DCF. D-DCF based on a hybrid virtual carrier sense mechanism maintains compatibility with DCF. In D-DCF, before sending any data-frames, the sender and receiver node transmit a pilot sequence by means of an omni-directional request-to-send/clear-to-send handshake mechanism. Based on the pilot, the directional beam can be formed by the smart antenna. Then the node can transmit its data-frame in the directional mode. The other nodes save the transmission time between the sender and receiver in the omni-directional mode in their network allocation vectors. When the sender and receiver communicate in the directional mode, the other nodes can access the channel to send their data-frames. Hence, D-DCF supports space division multiplexing. Moreover, D-DCF fully supports time division duplex, namely both the forward and backward transmission in one access period. Simulation results show that D-DCF can support the hybrid antenna system effectively and provide much higher network throughput, lower delay, jitter and packet-loss-rate than DCF does.