Spectrum Efficiency Maximization for Cooperative Power Beacon-Enabled Wireless Powered Communication Networks

We consider a spectrum efficiency(SE)maximization problem for cooperative power beacon-enabled wireless powered communication networks(CPB-WPCNs),where each transmitter harvests en-ergy from multi-antenna power beacons(PBs)and transmits data to the corresponding receiver.For data transmission,both orthogonal transmission,i.e.,the time splitting(TS)mode,and non-orthogonal trans-mission,i.e.,the interference channel(IC)mode,are considered.Aiming to improve the system SE,the energy beamformers of PBs,the transmit power,and the transmit time duration of transmitters are jointly optimized.For the TS mode,the original non-convex problem is transformed into a convex opti-mization problem by means of variable substitution and semidefinite relaxation(SDR).The rank-one na-ture of this SDR is proved,and then a Lagrange-dual based fast algorithm is proposed to obtain the opti-mal solution with much lower complexity.For the IC mode,to conquer the strong non-convexity of the problem,a branch-reduce-and-bound(BRB)mono-tonic optimization algorithm is designed as a bench-mark.Furthermore,a low-complexity distributed suc-cessive convex approximation(SCA)algorithm is pre-sented.Finally,simulation results validate the perfor-mance of the proposed algorithms,achieving optimal-ity within only 1%∼2%computation time compared to the CVX solver in the TS mode and achieving 98%of the optimal performance in the IC mode.

Cooperative communications with hierarchical modulation in downlink OFDMA based cellular networks

Cooperative transmission is a promising way to improve system performance in orthogonal frequency division multiple access (OFDMA) based cellular networks.This paper proposes two heuristic cooperation schemes including relay selection and resource allocation using hierarchical modulation (HM) to fully exploit the radio resources in cellular networks where user equipments (UEs) relay for each other.The relay selection procedure considers both the channel conditions and the energies left in relays to make the cooperative communications behave better.To mitigate the spectrum efficiency loss due to the half-duplex mode,the bits of relayaided UE and its relay (which is also a UE) are transmitted simultaneously in one sub-channel using HM to improve the utilization efficiency of sub-channels.Besides,time resources are used effectively with the adaptively changed proportion of the two sub-frames divided for relay transmission.Simulation results show that the proposed schemes can improve the spectrum efficiency compared with the traditional schemes.

A Greedy Algorithm for Task Offloading in Mobile Edge Computing System

Mobile edge computing(MEC) is a novel technique that can reduce mobiles' computational burden by tasks offloading, which emerges as a promising paradigm to provide computing capabilities in close proximity to mobile users. In this paper, we will study the scenario where multiple mobiles upload tasks to a MEC server in a sing cell, and allocating the limited server resources and wireless channels between mobiles becomes a challenge. We formulate the optimization problem for the energy saved on mobiles with the tasks being dividable, and utilize a greedy choice to solve the problem. A Select Maximum Saved Energy First(SMSEF) algorithm is proposed to realize the solving process. We examined the saved energy at different number of nodes and channels, and the results show that the proposed scheme can effectively help mobiles to save energy in the MEC system.

Cross-Layer Adaptive Resource Allocation Algorithm with Diverse QoS Requirements for Single-Cell OFDMA Systems

The orthogonal frequency division multiple access( OFDMA) based communication system has been considered as the main trend of next-Generation communication system. But the existing resource allocation algorithm designed for such system is always with high complexity thus hard to be realized. To solve such problem with the constraints of spectrum efficiency and buffer state,a novel cross-layer resource allocation algorithm( RAA) is proposed in this paper. The goal of our RAA is to maximize the system throughput while satisfying several practical constraints,such as fairness among services,head of line( Ho L) delay and diverse quality of service( Qo S) requirements. Due to these constraints,finding the optimal solution becomes a NPhard problem. Therefore in this paper a novel method to solve such problem with acceptable complexity is proposed within following steps: firstly,based on the link state we formulate the ideal subchannel allocation strategy as a convex optimization problem,which can be efficiently solved by our proposed lagrange multiplier technique subchannel allocation( LMTSA) algorithm; secondly,according to the obtained channel allocation matrix,a power allocation algorithm based on the water-filling power allocation( WPA) idea is deployed to get the optimal power allocation matrix combining with adaptive modulation and coding( AMC); finally,through a greedy algorithm,the ultimate subchannel and power allocation matrix can be obtained based on iterative method. The simulation results illustrate that we can achieve the higher throughput and better Qo S performance than the widely-used maximum throughput( MT) algorithm and round robin( RR) algorithm.

Clustering in the Wireless Channel with a Power Weighted Statistical Mixture Model in Indoor Scenario

Cluster-based channel model is the main stream of fifth generation mobile communications, thus the accuracy of clustering algorithm is important. Traditional Gaussian mixture model (GMM) does not consider the power information which is important for the channel multipath clustering. In this paper, a normalized power weighted GMM (PGMM) is introduced to model the channel multipath components (MPCs). With MPC power as a weighted factor, the PGMM can fit the MPCs in accordance with the cluster-based channel models. Firstly, expectation maximization (EM) algorithm is employed to optimize the PGMM parameters. Then, to further increase the searching ability of EM and choose the optimal number of components without resort to cross-validation, the variational Bayesian (VB) inference is employed. Finally, 28 GHz indoor channel measurement data is used to demonstrate the effectiveness of the PGMM clustering algorithm.

On Multi-Frequency Channel Interference Alignment of 3 Channels and 4 Users

This paper explores the multi-frequency independent channel interference alignment(MFC-IA) system of 3 channels and4 users,and single data stream transmit,i.e.(3×3,1)~4 system.We derive the analytic solution for(3×3,1)~4 MFC-IA system.Based on the analytic solution,an optimization problem is proposed aim at the optimal IA solution.Then based on such a math model,we propose a simulated annealing(SA) algorithm to search optimal IA solution.The simulation results show that the simulated annealing IA algorithm has a better sum rate performance than iterative maximize signal to interference plus noise ratio(Max-SINR) algorithm.This result can be extended to single data stream multi-antenna IA system with 3 antennas and4 users.

A New Codebook Design Scheme for Fast Beam Searching in Millimeter-Wave Communications

To overcome imperfection of exhaustive based beam searching scheme in IEEE 802.15.3c and IEEE 802.11 ad and accelerate the beam training process, combined with the fast beam searching algorithm previously proposed, this paper proposed a beam codebook design scheme for phased array to not only satisfy the fast beam searching algorithm's demand, but also make good use of the advantage of the searching algorithm. The simulation results prove that the proposed scheme not only performs well on flexibility and searching time complexity, but also has high success ratio.

An MAC Layer Aware Pseudonym (MAP) Scheme for the Software Defined Internet of Vehicles

This paper proposes a cross-layer design to enhance the location privacy under a coordinated medium access control(MAC) protocol for the Internet of Vehicles(Io V). The channel and pseudonym resources are both essential for transmission efficiency and privacy preservation in the Io V. Nevertheless, the MAC protocol and pseudonym scheme are usually studied separately, in which a new MAC layer semantic linking attack could be carried out by analyzing the vehicles' transmission patterns even if they change pseudonyms simultaneously. This paper presents a hierarchical architecture named as the software defined Internet of Vehicles(SDIV). Facilitated by the architecture, a MAC layer aware pseudonym(MAP) scheme is proposed to resist the new attack. In the MAP, RSU clouds coordinate vehicles to change their transmission slots and pseudonyms simultaneously in the mix-zones by measuring the privacy level quantitatively. Security analysis and extensive simulations are conducted to show that the scheme provides reliable safety message broadcasting, improves the location privacy and network throughput in the Io V.

Peer selecting model based on FCM for wireless distributed P2P files sharing systems

IIn order to improve the performance of wireless distributed peer-to-peer(P2P)files sharing systems,a general system architecture and a novel peer selecting model based on fuzzy cognitive maps(FCM)are proposed in this paper.The new model provides an effective approach on choosing an optimal peer from several resource discovering results for the best file transfer.Compared with the traditional min-hops scheme that uses hops as the only selecting criterion,the proposed model uses FCM to investigate the complex relationships among various relative factors in wireless environments and gives an overall evaluation score on the candidate.It also has strong scalability for being independent of specified P2P resource discovering protocols.Furthermore,a complete implementation is explained in concrete modules.The simulation results show that the proposed model is effective and feasible compared with min-hops scheme,with the success transfer rate increased by at least 20% and transfer time improved as high as 34%.

Robust Beamforming Under Channel Prediction Errors for Time-Varying MIMO System

The accuracy of acquired channel state information(CSI)for beamforming design is essential for achievable performance in multiple-input multiple-output(MIMO)systems.However,in a high-speed moving scene with time-division duplex(TDD)mode,the acquired CSI depending on the channel reciprocity is inevitably outdated,leading to outdated beamforming design and then performance degradation.In this paper,a robust beamforming design under channel prediction errors is proposed for a time-varying MIMO system to combat the degradation further,based on the channel prediction technique.Specifically,the statistical characteristics of historical channel prediction errors are exploited and modeled.Moreover,to deal with random error terms,deterministic equivalents are adopted to further explore potential beamforming gain through the statistical information and ultimately derive the robust design aiming at maximizing weighted sum-rate performance.Simulation results show that the proposed beamforming design can maintain outperformance during the downlink transmission time even when channels vary fast,compared with the traditional beamforming design.

Low Complexity Joint Hybrid Precoding for Millimeter Wave MIMO Systems

In millimeter wave(mmWave) multiple-input multiple-output(MIMO) systems, hybrid precoding has been widely used to overcome the severe propagation loss. In order to improve the spectrum efficiency with low complexity, we propose a joint hybrid precoding algorithm for single-user mmWave MIMO systems in this paper. By using the concept of equivalent channel, the proposed algorithm skillfully utilizes the idea of alternating optimization to complete the design of RF precoder and combiner. Then, the baseband precoder and combiner are computed by calculating the singular value decomposition of the equivalent channel. Simulation results demonstrate that the proposed algorithm can achieve satisfactory performance with quite low complexity. Moreover, we investigate the effects of quantization on the analog components and find that the proposed scheme is effective even with coarse quantization.

SDN Based Next Generation Mobile Network With Service Slicing and Trials

Software-Defined Network(SDN)empowers the evolution of Internet with the OpenFlow,Network Virtualization and Service Slicing strategies.With the fast increasing requirements of Mobile Internet services,the Internet and Mobile Networks go to the convergence.Mobile Networks can also get benefits from the SDN evolution to fulfill the Sth Generation(5G) capacity booming.The article implements SDN into Frameless Network Architecture(FNA) for5G Mobile Network evolution with proposed Mobile-oriented OpenFlow Protocol(MOFP).The Control Plane/User Plane(CP/UP)separation and adaptation strategy is proposed to support the User-Centric scenario in FNA.The traditional Base Station is separated with Central Processing Entity(CPE) and Antenna Element(AE) to perform the OpenFlow and Network Virtualization.The AEs are released as new resources for serving users.The mobile-oriented Service Slicing with different Quality of Service(QoS) classification is proposed and Resource Pooling based Virtualized Radio Resource Management(VRRM) is optimized for the Service Slicing strategy with resource-limited feature in Mobile Networks.The capacity gains are provided to show the merits of SDN based FNA.And the MiniNet based Trial Network with Service Slicing is implemented with experimental results.

Hybrid Precoder and Combiner Design with Finite Resolution PSs for mmWave MIMO Systems

Hybrid precoding and combining have been considered as a promising technology, which can provide a compromise between hardware complexity and system performance in millimeter wave multiple-input multiple-output systems. However, most existing hybrid precoder and combiner designs generally assume that infinite resolution phase shifters(PSs) are used to produce the analog beamformers. In a practical scene, the design with accurate PSs can lead to high hardware cost and power consumption. In this paper, we investigate the hybrid precoder and combiner design with finite resolution PSs in millimeter wave systems. We employ alternate optimization as the main strategy to jointly design analog precoder and combiner. In addition, we propose a low complexity algorithm, where the analog beamformers are implemented only by finite resolution PSs to maximize spectral efficiency. Then, the digital precoder and combiner are designed based on the obtained analog beamformers to improve the spectral efficiency. Finally, simulation results and mathematical analysis show that the proposed algorithm with low-resolution PSs can achieve near-optimal performance and have low complexity.

Always-optimally-coordinated candidate selection algorithm for peer-to-peer files sharing system in mobile self-organized networks

In order to improve the performance of peer-to-peer files sharing system under mobile distributed en-vironments,a novel always-optimally-coordinated(AOC)criterion and corresponding candidate selectionalgorithm are proposed in this paper.Compared with the traditional min-hops criterion,the new approachintroduces a fuzzy knowledge combination theory to investigate several important factors that influence filestransfer success rate and efficiency .Whereas the min-hops based protocols only ask the nearest candidatepeer for desired files,the selection algorithm based on AOC comprehensively considers users' preferencesand network requirements with flexible balancing rules.Furthermore,its advantage also expresses in theindependence of specified resource discovering protocols,allowing for scalability.The simulation resultsshow that when using the AOC based peer selection algorithm,system performance is much better thanthe min-hops scheme,with files successful transfer rate improved more than 50% and transfer time re-duced at least 20%.

Novel Grouped Probability Data Association Algorithm for MIMO Detection

To bridge the performance gap between original probability data association （PDA） algorithm and the optimum maximum a posterior （MAP） algorithm for multi-input multi-output （MIMO） detection, a grouped PDA （GP-PDA） detection algorithm is proposed. The proposed GP-PDA method divides all the transmit antennas into groups, and then updates the symbol probabilities group by group using PDA computations. In each group, joint a posterior probability （APP） is computed to obtain the APP of a single symbol in this group, like the MAP algorithm. Such new algorithm combines the characters of MAP and PDA. MAP and original PDA algorithm can be regarded as a special case of the proposed GP-PDA. Simulations show that the proposed GP-PDA provides a performance and complexity trade, off between original PDA and MAP algorithm.

Optimal power allocation for a video layered multicasting relay strategy in cellular system

Within a cell of cellular system,cooperative relay technique can improve the performance of multicast efficiently,but it can cause the stream frequent interruptions because of the mobility of relay terminals.A video layered cooperative relay strategy is proposed to guarantee the continuity of multicast stream and retain high-bandwidth of the cooperative relay channel.Based on the capacity analysis for layered relay channel in the strategy,the optimal power allocation is studied to maximize capacity.After analyzing and optimizing the capacity in abstract models,the study is extended to a non-fading and a Gaussian wireless channel model to satisfy the scenario of cellular system.Giving the relay nodes position or distribution of noise power,the obtained results can determine the optimal power allocation among the transmitter and relay nodes.At last,the simulation results show that the strategy and its optimal power allocation have a significant improvement on the performance.

Optimal power allocation for amplify-and-forward in single relay non-cooperative systems

For a single-relay amplify-and-forward (AF) non-cooperative system,an optimal power proportionbetween source and relay is considered.Aiming to minimize end-to-end bit error rate (BER) and maximizeattainable rate,both large-scale path loss and small-scale Rayleigh fading are taken into account.Aclosed form expression to allocate power in optimal proportion at source is obtained.Simulation resultsshow that the proposed scheme to distribute power can minimize BER under any channel conditions.

A novel spectrum prediction scheme based on SVM in cognitive radio networks

In cognitive radio networks, Secondary Users (SUs) have opportunities to access the spectrum channel when primary user would not use it, which will enhance the resource utilization. In order to avoid interference to primary users, it is very important and essential for SUs to sense the idle spectrum channels, but also it is very hard to detect all the channels in a short time due to the hardware restriction. This paper proposes a novel spectrum prediction scheme based on Support Vector Machines (SVM), to save the time and energy consumed by spectrum sensing via predicting the channels' state before detecting. Besides, spectrum utilization is further improved by using the cooperative mechanism, in which SUs could share spectrum channels' history state information and prediction results with neighbor nodes. The simulation results show that the algorithm has high prediction accuracy under the condition of small training sample case, and can obviously reduce the detecting energy, which also leads to the improvement of spectrum utilization.