Power Allocation for Self-Coded Distributed Space-Time Codes in FD Two-Way Relaying Networks

In spatial modulation (SM) systems, when channel state information is available at the transmitter, adaptive power allocation can be exploited to enhance the SM performance. In this paper, optimal power allocation in SM systems is considered from an information-theoretical view. First, as there is no closed-form expression of the SM capacity, the instantaneous mutual information is formulated in an analytic form for SM systems with two transmit antennas. Then, two power-allocation algorithms are proposed to maximize the SM mutual information. One is a sub-optimal power-allocation algorithm that is established in closed form to maximize the upper bound of SM mutual information. The other is an iterative algorithm for optimal power allocation that is proposed to achieve the maximum mutual information of SM systems while dramatically reducing the operational complexity compared with global computer searching. To evaluate the performance of the proposed power-allocation algorithms, numerical and simulation results are reported in terms of outage capacity and ergodic capacity, which demonstrates that the proposed power-allocation algorithms significantly improve the SM performance, compared with conventional equal-power allocation.

Power allocation in multi-hop OFDM transmission systems with amplify-and-forward relaying: A unified approach

Cache is becoming an effective method to improve the transmission rate and reduce the backhaul load. Nevertheless, owing to the limited capacity of backhaul, less power should be allocated to the users whose requested contents do not exist in the local caches to maximize the performance of the caching users. Thus, in this paper, power allocation (PA) is considered to further improve the performance of cache-aided small-cell networks with limited backhaul, where interference alignment is utilized to manage interferences among users. Specially, three PA algorithms are proposed. First, we come up with a PA algorithm to maximize the sum rate of the network, considering the limitation of backhaul. Then, in order to make more users meet their rate requirement, a PA algorithm to minimize the average outage probability is proposed. In addition, in order to further improve the users' experience, a PA algorithm to maximize the average satisfaction of all the users is also designed. Plenty of simulation results are provided to show the effectiveness of the three proposed PA algorithms.

This paper investigates the performance of a full-duplex (FD) relaying-enabled satellite sensor network under residual loop interference, where the satellite uplink and the downlink transmissions simultaneously occur over the same frequency band. Specifically, the closed-form expressions for the outage probability and ergodic capacity of the FD relaying satellite sensor network are derived by considering residual loop interference, channel statistical property, propagation loss, geometric satellite antenna pattern, and terminal elevation angle. Simulation results show the achieved performance gains of a full-duplex relaying satellite sensor network over traditional half-duplex relaying, and highlight the impact of key system parameters on the performance of the considered FD relaying satellite sensor network.

This paper focuses on the spectral efficiency (SE) problem in amplify-and-forward (AF) and decode-and-forward (DF) relaying cooperative systems with full-duplex (FD) operation. Previous works on FD relaying systems have focused on outage performance or relay selection schemes wherein for the max-min relay selection scheme residual loop-interference has been neglected. Therefore, the motivation of this paper is to figure out which one of the relaying methods, AF or DF, is spectrally efficient in terms of the single relay selection scheme. For this, we apply time-based distributed method for max-min relay selection scheme by considering the residual loop interferences. Moreover, to see the impact of overhead, we consider a non-ideal FD relaying cooperative system. Numerical and simulation results are provided to illustrate the effect of collisions on the SE and a comparison of SE between two relaying methods for the distributed method.

We consider multi-hop OFDM relaying systems employing either decode-and-forward (DF) or amplify-and-forward (AF) relaying protocols in this paper. We propose adaptive power allocation (PA) algorithms under joint transmit power constraint at source and relays in order to maximize system capacity with channel state information (CSI) known at all nodes. The paring of subcarriers is also discussed. Simulation results show that the proposed adaptive PA algorithms achieve higher system capacity than uniform PA algorithms. If paring techniques are employed, system capacity can be further enhanced.

Full duplex (FD) communication has emerged as an attractive solution for increasing the network throughput, by allowing downlink (DL) and uplink (UL) transmissions in the same spectrum. However, only employing FD base stations in heterogeneous cellular networks (HCNs) cause coverage reduction, due to the DL and UL interferences as well as the residual loop interference. We, therefore, propose HCNs with half duplex massive multiuser multiple-input multiple-output macrocell base stations (MBSs) to relax the coverage reduction, and FD small cell base stations (SBSs) to improve spectrum efficiency. A tractable framework of the proposed system is presented, which allows to derive exact and asymptotic expressions for the DL and the UL rate coverage probabilities, and the DL and the UL area spectral efficiencies (ASEs). Monte Carlo simulations confirm the accuracy of the analytical results, and it is revealed that the equipping massive number of antennas at MBSs enhances the DL rate coverage probability, whereas increasing FD SBSs increases the DL and the UL ASEs. The results also demonstrate that by tuning the UL fractional power control, a desirable performance in both UL and DL can be achieved.

This paper investigates the problem of non-cooperative game theoretic power allocation (NGTPA) for distributed multiple-radar architectures in a spectrum sharing environment, where multiple radars coexist with a communication system in the same frequency band. The primary objective of the multiple-radar system is to minimize the power consumption of each radar by optimizing the transmission power allocation, which is constrained by a predefined signal-to-interference-plus-noise ratio requirement for target detection and a maximum interference tolerant limit for communication system. Since each radar is rational and selfish to maximize its own utility, we utilize the non-cooperative game theoretic technique to tackle the distributed power allocation problem. Taking into consideration the target detection performance and received interference power at the communication receiver, a novel utility function is defined and employed as the optimization criterion for the NGTPA strategy. Furthermore, the existence and uniqueness of the proposed game’s Nash equilibrium point are analytically proved. An iterative power allocation algorithm with low computational complexity and fast convergence is developed, where the optimal value of each radar’s transmission power is simultaneously updated at the same time step. Numerical simulations are provided to verify the analysis and evaluate the performance of the proposed strategy as a function of the system parameters. It is shown that the distributed algorithm is effective for power allocation and could protect the communication system with limited implementation overhead.

The increasing use of relays in wireless communication systems is a driving force to explore innovative techniques that can improve the quality of service as well as enhance the coverage of wireless systems. Orthogonal frequency division multiple access (OFDMA) is widely deployed in broadband wireless systems to effectively combat the frequency selectivity of the wireless fading channel. Wireless relays are used in practical OFDM-based wireless systems such as WiMAX to increase the capacity and diversity order of the system. To fully exploit the benefits of OFDMA, relaying systems require efficient management of resources, including power and subcarriers. The difficulty in resource allocation in a relaying system is the nonconvexity of the optimization problem caused by the inter-relationship of all the resources through the relay station. Therefore, suboptimal and heuristic algorithms are proposed to assign power and subcarriers to the users in the relaying system while maintaining flexible fairness in resource allocation. In this dissertation, we improve the efficiency of subcarrier and power allocation algorithms with flexible fairness in the downlink of an amplify-and-forward (AF) OFDM relaying system. We propose an asymptotically fair subcarrier allocation algorithm that provides flexibility in the fairness index for possible improvement in the total throughput of the system by using a group-based approach. We investigate the problem of power allocation for an AF relaying scheme by considering three different objective functions: average SNR, average BER, and outage probability. The results are presented for various relay locations and different total power in the system. It is shown that the solution to the power allocation problem does not depend on the objective function when the relay is closer to the mobile user for different objective functions. By deriving the capacity of the AF relaying, a new parameter, called cooperation coefficient, is introduced to quantify the cooperation level from the relaying links in the data rate of the the mobile station. Assuming flat power allocation and using the cooperation coefficient parameter, a cooperative subcarrier allocation algorithm is proposed that increases the total throughput of a multi-user OFDM relaying system by approximately 15%. We also propose a two-step solution for subcarrier and power allocation of an AF relaying system. In the first step, the total power is allocated to the users and relays based on the power ratio found for the single-relay system. In the second step, subcarriers are assigned to the users based on the cooperative subcarrier allocation algorithms. Based on our finding, the total throughput of the system improves by 25% using the two-step procedure. By applying the proposed asymptotically fair idea to the two-step subcarrier and power allocation, we maintain a flexible fairness and further increase the total throughput in an OFDM relaying system.

To satisfy the increasing demands for high data-rate service of high-speed railway (HSR) users on the train, the most promising approach is to utilize the two-hop architecture. With this architecture, large amount of data will be transferred to the access point (AP) at which some data may need to be cached when the train approaches the cell edge. In this paper, an energy-efficiency buffer (EEB) power allocation scheme is proposed, which is able to achieve a high energy efficiency under the requirement of buffer size in HSR scenarios. Firstly, the energy-efficiency optimization problem is formulated as a fractional form. Secondly, this non-convex problem is resolved by transforming it into an equivalent one. Then an iterative power allocation algorithm is proposed and the optimal solution is obtained based on it. Finally, we analyze the effect of cache point on energy efficiency (EE) performance of the proposed EEB power allocation scheme. Furthermore, the relationship between the buffer size and EE performance of HSR communication system is presented. Simulation results suggest that the proposed EEB power allocation scheme can achieve the optimal energy-efficient performance.

In this letter, we address the problem of energy efficient coordinated power allocation in a multicell distributed antenna system (DAS). Due to the mutual coupling of multiple cells caused by intercell interference (ICI), the problem is nonconvex and, therefore, is difficult to solve. We assume that only the large-scale channel state information at the transmitter (CSIT) is known to reduce the system cost. Using successive Taylor expansion, we formulate the problem as a series of quasi-concave fractional programming subproblems. These subproblems are further solved using an iterative power allocation algorithm. The proposed solution is superior to existing methods, as verified by simulation results.

The cognitive radio technology aims to increase the spectrum utilization by accessing opportunistically the unused spectrum bands. Multicarrier communications are considered to be used in cognitive radio systems. In cognitive radio systems, the power allocation should be carried out within the cognitive radio network so that no excessive interference is caused to the primary user. In this paper, an iterative power allocation algorithm is proposed to maximize the downlink capacity of the cognitive radio system under both the total power budget and interference introduced to the primary user constraints. Moreover, two complexity reduced algorithms are presented. The problem of channel allocation in multiuser cognitive radio networks is discussed. Finally, the performance of the proposed algorithms is investigated using computer simulations.KeywordsCognitive RadioPower AllocationOrthogonal Frequency Division Multiplex SystemCognitive Radio SystemSubcarrier AllocationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

LoRa has been recognized as one of the most promising low-power wide-area (LPWA) techniques. Since LoRa devices are usually powered by batteries, energy efficiency (EE) is an essential consideration. In this paper, we investigate the energy efficient resource allocation in LoRa networks to maximize the system EE (SEE) and the minimal EE (MEE) of LoRa users, respectively. Specifically, our objective is to maximize the corresponding EE by jointly exploiting user scheduling, spreading factor (SF) assignment, and transmit power allocations. To solve them efficiently, we first propose a suboptimal algorithm, including the low-complexity user scheduling scheme based on matching theory and the heuristic SF assignment approach for LoRa users scheduled on the same channel. Then, to deal with the power allocation, an optimal algorithm is proposed to maximize the SEE. To maximize the MEE of LoRa users assigned to the same channel, an iterative power allocation algorithm based on the generalized fractional programming and sequential convex programming is proposed. Numerical results show that the proposed user scheduling algorithm achieves near-optimal EE performance, and the proposed power allocation algorithms outperform the benchmarks.

To promote future intelligent systems, a novel cyber-physical-social smart system (CPS3) powered by the Internet of Things is presented in this paper, where wireless network virtualization is adopted to enhance the diversity and the flexibility of the service operation and the system management. Based on the presented system, a robust energy-efficient resource allocation scheme is proposed to guarantee the outage probability requirements of controllers and actuators while realizing the maximization of the system energy efficiency. Different from the existing works, imperfect channel state information is studied for energy-efficient resource allocation in CPS3. To effectively handle the formulated optimization problem, the concept of virtual devices is introduced to equivalently reformulate the original problem. Afterward, the probabilistic mixed problem is approximately transformed into a nonprobabilistic problem though outage probability analyses. After the transformation, the optimization problem can be decomposed into power allocation and channel allocation, where an iterative algorithm for power allocation is adopted to maximize the system energy, and a heuristic greedy algorithm is presented to schedule sensors and actuators on different subchannels based on the obtained power allocation results. Simulation results demonstrate the convergency of the proposed algorithm and the advantages of the proposed scheme.

The following paper investigates the secondary sum rate of MIMO two-way cognitive relay networks with multiple relays using amplify and forward (AF) strategy. The capacity of the system can be maximize by using optimum power allocation (OPA) algorithm in place of equal power allocation(EPA) among all nodes, while assuming that all node having fully channel state information (CSI). It has been considered that MIMO cognitive relay with spectrum sharing and cooperative strategy between node to maximize the secondary sum rate and enormous use of the spectrum. Our aim is to maximize the secondary sum rate and efficient spectrum use. MIMO relay is going to use amplify and forward relay technique means relay is not decode the signal received from the secondary user's. Result shows that this technique is increasing the secondary sum rate without using extra power and spectrum.