A low power register scheduling and allocation algorithm for multiple voltage

The graph-coloring approach for register allocation has been widely used but its formulation is too abstract to generate efficient spill code. Recently, a new register allocation based on the analysis of variable reference flow was proposed [13]. This register allocation leads to more efficient spill code (i.e, reduced spill instructions) than the graph-coloring approach, but requires a large amount of computation. For the trade-off between the computation amount and code efficiency, this paper proposes two variations of the register allocation proposed in [13]. The first register allocation technique reduces computation time by employing a simplified graph-coloring algorithm for variable register allocation. The second technique generates more efficient code with aggressive variable flow analysis demanding a large amount of computation than [13]. Experimental results show that the first allocation reduces the amount of spill code by 22.2% and the amount of computation by 20.4% when compared to the Briggs’ allocator. The second allocator improves the efficiency by 6.2% with the increase of the computation by 4.6 times when compared to the register allocation in [13].

A new algorithm named the time-zone algorithm for solving register allocation problem in the automatic data path synthesis is presented in this paper. The time-zone algorithm was developed from the left-edge algorithm with which the number of registers can be minimized. The time-zone algorithm was developed to minimize the number of registers as well as the interconnections and the number of multiplexers required for the registers. The experimental results obtained from testing several published examples show that the interconnections are improved and the number of multiplexers is reduced while at the same time the number of registers is still minimized.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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.

In this article, a novel multiple-input multiple-out (MIMO) transmission scheme, called generalized polarized enhanced spatial modulation (GPESM), is proposed for dual-polarized land mobile satellite (LMS) communications. We first introduce the enhanced spatial modulation (ESM) technique for dual-polarized LMS communications, in which polarization dimension, spatial dimension and multiple signal constellations are used to transmit information and obtain substantial performance gain. Meanwhile, the theoretical upper bound for the average bit error probability (ABEP) of the proposed GPESM scheme is derived. In order to further improve the reliability of the system, we also propose two novel power allocation (PA) algorithms for GPESM system, which are the optimization-driven approximated max-min distance (AMMD)-based PA algorithm and the data-driven deep neural network (DNN)-based PA algorithm. To achieve an enhanced spatial diversity gain, we consider to apply a reconfigurable intelligent surface (RIS) to the GPESM system as a relay to assist in transmitting information. In this way, the user can receive the information transmitted by the satellite on one hand, and the information sent by the satellite via the RIS relay on the other hand. We also extend the above-mentioned two PA algorithms to the RIS-assisted GPESM systems. Our simulation results show that the RIS-assisted GPESM systems are capable of obtaining high bit error rate (BER) performance gain (up to 10 dB) compared to the standard GPESM system and two PA algorithms can further improve the performance to the systems.

Adaptive channel and power allocation of downlink multi-user MC-CDMA systems

In this paper, we propose a high efficiency algorithm of power and bit allocation for orthogonal frequency division multiple access (OFDMA) system, in which the allocation procedure is divided into three parts: linear water-filling power allocation, bit allocation and power and bit adjustment. It can quickly achieve the power and bit allocation on the user's sub-carrier level with a good fairness performance. Simulation results show that the proposed algorithm can obviously decrease the operation complexity and slightly descended system throughput contrast to other algorithms. It is a promising algorithm to be used in a practical system for radio resource allocation.

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.

In conventional multicast scheme (CMS), the total throughput of multicast group is constrained by the user with the worst channel quality. In order to overcome this problem of limited throughput, the authors introduce a resource allocation algorithm by exploiting layered coding combined with erasure correction coding for multicast services in the downlink of orthogonal frequency-division multiple access-based multi-antenna system. To reduce the feedback overhead of uplink, the authors design a novel transmission scheme with limited feedback. Then, the joint subcarrier and power allocation problem for the data of base layer and enhancement layers are formulated, which is shown to be non-deterministic polynomial- hard. Hence, in order to reduce the computational complexity, they propose a three-phase suboptimal algorithm. The algorithm is designed to maximise the system throughput, whereas at the same time guarantee the quality of services (QoS) requirements of all multicast groups. It is composed of precoding scheme, proportional fairness subcarrier allocation algorithm and modified water-filling power allocation algorithm with QoS guarantees (MWF-Q). To further decrease the complexity of MWF-Q, a power allocation algorithm with increased fixed power allocation algorithm with QoS guarantees is introduced. Simulation results show that the proposed algorithms based on limited feedback scheme significantly outperform CMS and any other existing algorithm with full feedback. Moreover, the proposed scheme can efficiently reduce 50% of the full feedback overhead.

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.

Like IoT or 5G networks, future multi-beam satellite (MBS) network becomes denser causing the number of beams increases. In addition, the characteristics of traffic requests in the MBS network is asymmetric distribution and time-varying. In view of above condition, a significant challenge power allocation facing is matching the traffic requests while with fairness into consideration as the network scales up. In this paper, we consider optimum power allocation based on traffic demands service for multi-beam satellite system, which has been formulated as an optimization problem in pursuit of traffic matching degree and fairness maximization. The optimal solution to this optimization problem can be obtained by the conjecture-based multi-agent Q-learning power allocation (MAQ-PA) algorithm. Simulated results show the effectiveness of the proposed power allocation algorithm.

Most resource allocation algorithms are based on interference power constraint in cognitive radio networks. Instead of using conventional primary user interference constraint, we give a new criterion called allowable signal to interference plus noise ratio (SINR) loss constraint in cognitive transmission to protect primary users. Considering power allocation problem for cognitive users over flat fading channels, in order to maximize throughput of cognitive users subject to the allowable SINR loss constraint and maximum transmit power for each cognitive user, we propose a new power allocation algorithm. The comparison of computer simulation between our proposed algorithm and the algorithm based on interference power constraint is provided to show that it gets more throughput and provides stability to cognitive radio networks.

We study the problem of admission control and resource (subcarriers, power and bit-loading) allocation in a heterogeneous OFDMA wireless network serving both QoS-constrained high-priority users and best-effort users. By clustering subcarriers, efficient algorithms for cluster and power allocation have been proposed. Our strategy maximizes the total network utility of the best-effort users while satisfying the QoS request for maximum number of high-priority users. We approximate best-effort user utility function as a piece-wise linear function and propose a linear programming based cluster allocation algorithm. The feasibility of the resource allocation problem depends on the number of HP users in the network. Since a large number of demanding HP users would render the resource allocation problem infeasible, a joint admission control and resource allocation scheme could be an efficient way of tackling both problems with less overhead. By incorporating admission control, we propose an efficient and optimal joint admission control and resource allocation algorithm.

Research on the low complexity adaptive power allocation algorithm in cooperative systems

To improve the resource utilisation of traditional two-way wireless relay system, an optimal power allocation (OPA) algorithm for a space-time cooperative network coding scheme employing amplify-and-forward protocol (AF-ST-CNC) is proposed. The system performance in terms of outage probability and its approximation in high signal-to-noise (SNR) regimes are first derived, and with minimising the larger outage probability of the two sources, the optimal power factors are obtained by using an iterative algorithm. Moreover, the closed-form solutions of the optimal power allocation factor under some special scenarios are given. The proposed algorithm only needs the average channel gain information and has low computation complexity, which facilitates the practical implementation. Simulation results show that, the proposed AF-ST-CNC with OPA algorithm outperforms the AF-ST-CNC with equal power allocation (EPA) algorithm and the space-time cooperative network coding scheme employing amplify-and-forward protocol (DF-ST-CNC) with OPA algorithm in terms of outage performance and symbol error rate (SER) performance.

To improve the resource utilization of traditional two-way wireless relay system, an optimal power allocation (OPA) algorithm for a space-time cooperative network coding scheme employing amplify-and-forward protocol (AF-ST-CNC) is proposed. The system performance in terms of outage probability and its approximation in high signal-to-noise (SNR) regimes are first derived, and by minimizing the larger outage probability of the two sources with respect to the characteristic of network coding, optimal power factors are obtained for some special cases are presented. The proposed algorithm only needs the average channel gain information and has low computation complexity, which facilitates the practical implementation. Simulation results show that the proposed AF-ST-CNC with OPA algorithm outperforms the AF-ST-CNC with equal power allocation (EPA) algorithm and the space-time cooperative network coding scheme employing amplify-and-forward protocol (DF-ST-CNC) with OPA algorithm in terms of outage performance.