Resource Allocation and Power Control for Mobile Relay in TDD-OFDMA Downlink

The IEEE 802.16j mobile multi-hop relay (MMR) is studied to improve throughput, extend coverage, and increase capacity. Mobile relay stations attached to vehicles make arbitrary movements and have interference with other base stations or relay stations, thus lowering service functions. This study sets out to suggest an interference detection and avoidance method and evaluates its performance in order to help introduce a mobile relay station for vehicle mounting in a mobile multi-hop relay network. The proposed approach would be implemented by the addition of MAC management messages at a base or relay station instead of the change of mobile station.

A new scheme is proposed to compensate the multiple Doppler frequency offsets (DFOs) for high-mobility OFDM uplink transmissions in this paper. According to the characteristics of uplink transmission, we find it is a good choice to solve the multiple DFOs problem in the spatial-domain. The proposed scheme consists of a mobile relay station (MRS) between the base station (BS) and the mobile terminal (MT). The MRS is immobile respect to the MT, and hence the DFOs are only generated between the MRS and the BS. The MRS uses an antenna array to transmit signals through different paths. The DFOs are estimated during the downlink, and the DFO for each path is separately compensated before the particular transmit beamforming for this path. Therefore, all the signals in different paths are superimposed at the BS without DFO, and the BS does not have to be changed in this case of high-mobility scenarios. The effectiveness of the proposed scheme is verified by simulations.

Wireless Relay networks have become very important technologies in the future wireless systems. Current research works mostly focus on scenarios where relay stations are either stationary or mobile with uniform velocity. However, in many applications, relay stations are mobile with irregular patterns. In particular, when mobile relay stations (MRSs) are deployed to complement the cellular systems, many issues such as handoff should be carefully investigated. In this paper, we focus on the handoff problem and propose a new handoff decision algorithm based on the relative velocities of user equipment (UE) to the serving access point (AP) and the target AP. We have show that the proposed handoff algorithm can significantly improve the handoff successful rate when the mobile relay station changes its moving patterns.

Cognitive radio and heterogeneous wireless networks are important candidate techniques for the fifth generation (5G) communication systems. On the other hand, propagation properties of radio channels in a physical layer are exploited to design efficient secure transmission schemes for 5G wireless networks. In this work, a security-aware joint power and subchannel allocation problem based on the inter-network cooperation is investigated at cognitive heterogeneous networks via imperfect spectral sensing. The security-aware joint power and subchannel allocation is subject to constraints in available subchannels, proportional fairness secrecy transmission rates among secondary mobile terminals (MTs), total interference power threshold, and total power for each secondary MT. In order to determine the impact of imperfect spectral sensing to resource allocation, we first represent the interference power at primary base station in terms of the misdetection probability and false alarm probability. Then, the security-aware power and subchannel allocation problem with inter-network cooperation is formulated as a biconvex optimization problem, and an optimal security-aware power and subchannel allocation algorithm is proposed utilizing the dual decomposition method. Compared to the heuristic power and subchannel allocation algorithms, numerical simulation results show that the proposed algorithms improve the total secrecy throughput and guarantee the proportional fairness among different secondary MTs.

Air-based Multi-hop Sensor Network for the Localization of Persons

Leveraging unmanned aerial vehicles (UAVs) for access and high altitude platform stations (HAPSs) for data backhaul to construct the Air-Ground Integrated Network (AGIN), is a feasible solution to achieve seamless network coverage for remote IoT devices in future 6 G era. However, since the number of terminals increases exponentially, it is essential to improve spectrum efficiency and throughput of the system. In addition, the limited on-board energy storage of UAVs and finite battery of IoT terminals make the system energy efficiency (EE) a new concern. To cope with the above mentioned challenges, in this study we first put forward a clustered-NOMA (C-NOMA)-enabled heterogeneous AGIN model for remote areas including one HAPS for backhaul and multiple UAVs for access, where C-NOMA is used to obtain both improved system throughput and terminal complexity. Then, we study the joint UAV trajectory plan and resource allocation problem in order to maximize the system EE. Since it is a mixed integer nonlinear programming (MINLP) issue coupled with transmission power, subchannel allocation, UAV trajectory and speed control, this problem is decoupled into two subproblems and solved iteratively. For the first one, the optimal channel and power strategy is obtained by our subchannel allocation and power control for AGIN EE (SAPAE) maximum algorithm according to Lagrange dual decomposition method. For the second, for transforming the nonconvex problem into a convex one, we provide the successive convex approximation-based UAV trajectory and speed optimization for AGIN EE (SUTSAE) maximum algorithm, and then the near-optimal UAV trajectory and flight speed are obtained. We conduct extensive experiments to compare with other benchmark methods. It is shown that the proposed approach is better in EE and spectrum efficiency.

Physical-layer network coding (PNC) promises a significant gain In overall network throughput for multi-user cooperative communications. In a multi-unicast scenario, one drawback associated with PNC is an additional noise term, coined as network coding (NC) noise, which severely degrades the system data rate. In this paper, our contribution to address this challenging problem is source and relay power control with the objective of maximization of the minimum average achievable rate among all the source-destination pairs subject to a given total power constraint. We further develop a joint power allocation and relay selection scheme, which only rely on long-term channel statistics, to extend our results to general network topologies. We show that the joint optimization problem can be divided into two problems: optimal power allocation and optimal relay selection where the former is scalable and leads to a power assignment algorithm that exhibits the same optimization complexity for any number of sources in the network and the latter can be performed in a decentralized manner. By means of simulations, we validate our theoretical developments and verify the efficiency of our algorithm in improving the average achievable rate compared to a multi-unicast system with no power control or relay selection. We conclude that the proposed algorithm largely combats the adverse effects of NC noise while achieving near optimal fairness.

The Proportional Fair (PF) scheduler has been extensively studied in wireless communications research. Most of the research done, however, focuses on theoretical or simplistic simulations. In this paper, both theory and practical measurements for a PF scheduler are studied. Two data collections are conducted to verify the performance of the scheduler in an actual LTE-A network (small cells) environment. Allocated Physical Resource Blocks (PRBs) and throughput of each phone used in the data collection are estimated. Three different types of PF schedulers are implemented to predict user throughput. The results show that the scheduler maintains good fairness for both user throughputs and PRB allocation. Further it is shown that our results, derived from actual recorded data are different from those derived from simulation models presented in the literature [1] [2]. Similarly, the cell throughput and fairness values are dynamic and randomly distributed with the time in an actual LTE-A network in contrast to simulation models. From our study, we show that the generalize PF Scheduler performs more accurately to predict the user throughput values. It is concluded that this real-world LTE-A network study is more meaningful and valuable in enhancing the understanding of actual 4G and future 5G networks.

In this paper, we propose a distributed beamforming approach to full-duplex relay (FDR) in multiuser multiple-input multiple-output (MIMO) relaying systems. In the proposed scheme, each mobile station (MS) and relay station (RS) performs distributed transmit beamforming and receive combining to suppress the self-interference at the RS as well as the multiuser interference at the MS's, while the base station (BS) performs zero-forcing beamforming with water-filling power allocation. Using the channel reciprocity between the uplink and downlink in time division duplex (TDD) systems, the distributed beamforming is realized in an iterative way without the need for additional information exchange among nodes. Numerical results are presented to verify that the proposed scheme provides substantial performance improvement compared with the half-duplex relay (HDR).

Macrocells may suffer serious uplink interference introduced by the deployment of co-channel femtocells. In this paper, an interference-aware pricing-based resource allocation algorithm for co-channel femtocells is proposed to alleviate their interference to macrocells without degrading the femtocell's capacity. The subchannel and power allocation problem is modeled as a non-cooperative game. A suboptimal subchannel allocation algorithm and an optimal power allocation algorithm are proposed to implement the resource allocation game. Simulation results show that the proposed algorithm not only improves the capacity of the macrocell but also the total capacity of the two-tier network, as compared with the unpriced subchannel allocation and Modified Iterative Water Filling (MIWF) power allocation algorithm.

Cooperative communication has great potential to improve the wireless channel capacity by exploiting the antennas on wireless devices for spatial diversity. The performance in cooperative communication depends on careful resource allocation such as relay selection and power control. In this paper, the network is expanded and more than one source is used. What is proposed is a distributed buyer/seller game theoretic framework over multiuser cooperative communication networks in order to stimulate cooperation and improve the system performance. A two-level Stackelberg game is employed to jointly consider the benefits of the source node and the relay nodes in which the source node is modeled as a buyer and the relay nodes are modeled as sellers, respectively. In this work we proposed coded method in which relays amplify and code Source data and send it to destination at the same time and then signal detection occur in destination, but in the codeless network relays send source data separately to destination. So, here coded and codeless networks are compared and contrasted. The stimulation results revealed that the proposed coded method performed better than the codeless ones; furthermore, the research shows that relays near the sources can play a significant role in increasing source node's utility, so every source would like to buy more power from these preferred relays. Also, the proposed algorithm enforces truthful power demands.

The two-tier femtocell network is comprised of a central macrocell underlaid with shorter range femtocell hotspots. Due to the universal frequency reuse, this kind of new system architecture brings about urgent problems of the interference management and the resource allocation. Motivated by these problems, the following contributions are made in this paper: 1) a novel joint power and subchannel allocation problem for Orthogonal Frequency Division Multiple Access (OFDMA) downlink based femtocells is formulated on the premise of minimizing Femto BSs' radiating interference; 2) a pseudo-handover based scheduling information exchange method is proposed to avoid the collision interference; 3) an iterative scheme of subchannel allocation and power control is proposed to solve the formulated problem, which is an NP-complete problem. Through simulations and comparisons with three other schemes, the proposed scheme shows better performance in reducing interference and the Femto BS's transmit power, and improving the spectrum efficiency.

In this paper, cell searching and direction-of-arrival (DoA) estimation methods are proposed for mobile relay stations with a uniform linear arrays in OFDM-based cellular systems. The proposed methods can improve the performance of cell searching and DoA estimation, even when there exist symbol timing offsets among the signals received from adjacent base stations and Doppler frequency shifts caused by the movement of the mobile relay station. The performances and computational complexities of the proposed cell searching and DoA estimation methods are evaluated by computer simulation under a mobile WiMAX environment.

In this letter, a mobile relay station (MRS) for vehicles with beamforming antennas is considered to increase the reliability of transmission link, especially for the MRS at cell boundary. Joint methods for cell searching and DoA estimation are proposed to form a beam in the direction of target BS while nulling interferences from adjacent BSs, especially for IP-based cellular systems employing break-before-make handover or make-before-break handover. The proposed cell searching and DoA estimation methods are evaluated by computer simulation under the environment of IEEE 802.16e (WiBro).

During channel modeling for high-mobility channels, such as high-speed train (HST) channels, the velocity of the mobile radio station is assumed to be constant. However, this might not be realistic due to the dynamic movement of the train along the track. Therefore, in this paper, an enhanced Gauss–Markov mobility model with a 3D non-stationary geometry based stochastic model (GBSM) for HST in MIMO Wireless Channels is proposed. The non-isotropic scatterers within a cluster are assumed to be around the sphere in which the mobile relay station (MRS) is located. The multi-path components (MPCs) are modeled with varying velocities, whereas the mobility model is a function of time. The MPCs are represented in a death–birth cluster using the Markov process. Furthermore, the channel statistics, i.e., the space-time correlation function, the root-mean-square Doppler shift, and the quasi-stationary interval, are derived from the non-stationary model. The model shows how the quasi-stationary time increases from 0.21 to 0.451 s with a decreasing acceleration of 0.6 to 0.2 m/s of the HST. In addition, the impact of the distribution of the angles on the channel statistics is presented. Finally, the simulated results are compared with the measured results. Therefore, there is a close relationship between the proposed model and the measured results, and the model can be used to characterize the channel’s properties.