Water-filling Power Allocation Algorithm Research Articles

Channel Customization for Joint Tx-RISs-Rx Design in Hybrid mmWave Systems

In strong line-of-sight millimeter-wave (mmWave) wireless systems, the rank-deficient channel severely hampers spatial multiplexing. To address this inherent deficiency, distributed reconfigurable intelligent surfaces (RISs) are introduced in this study to customize the wireless channel. Capitalizing on the ability of the RIS to reshape electromagnetic waves, we theoretically show that a favorable channel with an arbitrary tunable rank and a minimized truncated condition number can be established by elaborately designing the placement and reflection matrix of RISs. Different from existing works on distributed RISs, the number of elements needed for each RIS to combat the path loss and the limited phase control is also considered in this research. On the basis of the proposed channel customization, a joint transmitter-RISs-receiver (Tx-RISs-Rx) design under a hybrid mmWave system is investigated to maximize the downlink spectral efficiency. Using the proposed scheme, the optimal singular value decomposition-based hybrid beamforming at the Tx and Rx can be easily obtained without matrix decomposition for the digital and analog beamforming. The bottoms of the sub-channel mode in the water-filling power allocation algorithm, which are conventionally uncontrollable when the noise power is fixed, are proven to be independently adjustable by RISs. Moreover, the transmit power required for realizing multi-stream transmission is derived. Numerical results are presented to verify our theoretical analysis and exhibit substantial gains over systems without RISs.

Energy-Efficient Multi-Antenna Hybrid Block Diagonalization Precoding and Combining for MmWave Massive Multi-User MIMO Systems

The millimeter-wave (mmWave) massive multi-user multiple-input multiple-output (MU-MIMO) can significantly improve the throughput and spectral efficiency by equipping multi-antenna at both the base station (BS) and the users, which is greatly promising technologies for wireless communication systems. However, the large hardware requirement and high energy consumption are great hindrances. To effectively reduce the hardware and computational complexity and achieve a better trade-off between system complexity and performance, we propose an energy-efficient split sub-connected architecture based multi-user hybrid block diagonalization (BD) precoding and combining (Sub MU-HBD) scheme. The proposed Sub MU-HBD scheme employs the split sub-connected architecture to reduce the hardware complexity and improve spectral efficiency. Additionally, to significantly reduce the inter-user interference and further lessen the computational complexity, a low-dimensional digital precoding and combining scheme based on the BD is proposed. Furthermore, we propose a proportional water-filling power allocation algorithm to ensure optimal power distribution to users and improve energy efficiency. The simulation results demonstrate that the proposed Sub MU-HBD scheme can achieve near-optimal, and at times even better performance than some existing schemes.

Improved Tomlinson–Harashima Precoding for Ultra Reliable Communication in Intelligent Transportation Systems

Cyber-physical systems (CPSs) are characterized by integrating computation and physical processes. To cope with the challenges of the application of the CPSs in all kinds of environments, especially the cellular vehicle-to-everything (C-V2X) which needs high quality end-to-end communication, the robustness and reliability for CPSs are very crucial. Aiming at the technical challenges of information transmission caused by the fading effect and the fast time-varying characteristics of the channel for C-V2X communication, an improved Tomlinson–Harashima precoding (THP) algorithm for multiple input multiple output (MIMO) systems is proposed. Channel state information (CSI) and correlation are exploited to compensate instantaneous CSI, which could reflect current real-time channel status exactly. Further, the iterative water filling power allocation algorithm and the multiuser scheduling algorithm based on the greedy algorithm are jointly optimized and applied to the THP, which could improve the system performance. Simulation results show that the proposed algorithm can be efficiently applied to high-speed mobility scenarios and improve bit error ratio (BER) performance as well as spectrum utilization.

Research on PDMA communication system based on complete complementary sequence

Pattern division multiple access (PDMA) is a new non-orthogonal multiple access (NOMA) technology. It is proposed to meet the challenge of 5G large-scale connectivity and high-frequency spectral efficiency. Compared with traditional orthogonal multiple access (OMA), PDMA can support more users through the allocation of non-orthogonal resources. Due to perfect aperiodic correlation, complete complementary sequence (CCS) greatly improves the spectrum efficiency of the system. It has been widely used in wireless communication and radar sensing, and it still has research value in 5G. In order to apply the advantages of CCS to NOMA communication system, this paper proposes a system model of CCS spread spectrum coding based on PDMA. CCS is used as spread spectrum code to improve the performance of PDMA communication system. At the same time, on the basis of spread spectrum technology, this paper analyzes the average power allocation algorithm and water-filling power allocation algorithm, and a dynamic power allocation algorithm based on the transmission rate and practical application is proposed. The simulation results show that the system model can effectively improve the performance of the system.

Resource and power allocation for achieving rate fairness in D2D communications overlaying cellular networks

This paper presents a novel resource and power allocation scheme for device-to-device (D2D) communications overlaying cellular networks. The proposed scheme is implemented in two consecutive steps. The first step depends on implementing a vital algorithm that guarantees fairness in resource allocation among different D2D pairs by allocating the best subcarriers for every user such that every link’s data rate requirements can be satisfied. The second step utilizes the water-filling algorithm for power allocation among the subcarriers allocated to a certain link. The proposed scheme achieves high fairness with acceptable performance compared to rival algorithms in the literature. The simulation results show that the proposed algorithm outperforms the best subcarrier channel state information resource allocation scheme and the subcarrier achievable data rate scheme in terms of Jain’s fairness index.

SVD-based IWFA for next generation wireless MIMO communication

Abstract Point-to-point MIMO systems without channel state information at the transmitter (No CSIT) and with perfect channel state information at the transmitter (Perfect CSIT) were considered for the application of a novel singular-value-decomposition-based (SVD-based) iterative water-filling algorithm (IWFA). The optimal transmit power was computed for Rayleigh fading-based eigenchannels using an estimated iterative water-filling power allocation algorithm to maximize ergodic capacity. The results obtained with the proposed method showed significant improvements in ergodic capacity compared with the average power allocation method.

Energy Efficiency Optimization for Uplink Multiuser MIMO Systems

To satisfy green communication needs, energy efficiency is regraded as one of the most important indicators to evaluate the effectiveness of a communication system. In this paper, we establish the energy efficiency optimization framework for uplink multiuser mutliple-input multiple-output system. Taking the circuit power, the antenna link power and signal processing power into consideration, an analytical expression of the achieveable energy efficiency is firstly established, which can better model the practical communication process. Furthermore, we simplify the objective function under some mild conditions. After demonstrating the existence of a unique golbally optimal energy efficiency, an adaptive water-filling power allocation algorithm is proposed to further improve the energey efficiency of the system. Finally some simulation results are given to verify the performance of our scheme. Our work can provide a fundamental principles for uplink mutiluser multiple-input multiple-output systems design.

Combinatorial Resource Allocation Using Submodularity of Waterfilling

We show that the maximum mutual information (capacity) of parallel Gaussian channels obtained by the optimal water-filling algorithm for power allocation under a sum-power constraint is submodular. For a given power allocation, mutual information is known to be submodular. However, establishing the submodularity of the capacity, which additionally involves maximization of the mutual information over the power allocation, is challenging. Capacity of parallel Gaussian channels is equivalent to the maximum log-utility function used in resource allocation problems. Using this correspondence and the submodularity of the capacity, we find provable guarantees on multiple combinatorial resource allocation problems in wireless networks. In particular, we show that greedy algorithms give a 2-approximation for uplink OFDMA power and subcarrier allocation, FDMA capacity, downlink base-station association, with honest as well as strategic users who may or may not report their channel gains truthfully.

Aadptive Subcarrier Allocation for Multiple Cognitive Users over Fading Channels

In Cognitive Radio Network (CRN), where Primary User (PU) and multiple Secondary Users (SUs) wish to communicate with their corresponding receivers simultaneously over fading channels, spectrum utilization and efficient resource allocation are both significant points for CRN. Interference between PU and SUs should be eliminated in order to realize spectrum sharing. Multi-user resource allocation with the target of maximizing the spectral efficiency of SUs and satisfying the proportional rate constraint between SUs are proposed under the conditions of total SU interference constraint. An adaptive low-complexity suboptimal algorithm for subcarrier and power joint allocation is presented based on Rate Adaptive (RA) criterion, where adaptive subcarrier allocation is performed by assuming equal power distribution, while each subcarrier is assigned in accordance with subcarrier efficiency function. Moreover, linear water-filling algorithm for power allocation is applied within each subcarrier. Simulation results indicate that, with the proposed adaptive subcarrier allocation, spectral efficiency of multiple SUs is superior to traditional subcarrier power joint allocation algorithm. Low computational complexity and adaptive features make it available for implementation.

Resource Allocation with Limited Feedback and Joint Coding Scheme for Wireless Multi-antenna Multicast 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, we introduce a resource allocation algorithm by exploiting layered coding combined with erasure correction coding for multicast services in the downlink of OFDMA-based multi-antenna system. To reduce the feedback overhead of uplink, we design a novel transmission scheme with limited feedback. Then, we formulate the joint subcarrier and power allocation problem for the data of base layer and enhancement layers, which is shown to be NP hard. Hence, in order to reduce the computational complexity, we propose a three-phase suboptimal algorithm. The algorithm is designed to maximize the system throughput while 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.

Dynamic resource allocation with precoding and joint coding scheme for limited feedback‐based wireless multi‐antenna multicast 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.

Two-dimensional water-filling power allocation algorithm for MIMO-OFDM systems

Departing from the narrowband channel model, more and more researchers have recently considered the application of multiple-input multiple-output (MIMO) systems over frequency-selective fading channels in combination with the orthogonal frequency-division multiplexing (OFDM) technique. In this paper, we focus on the capacity of MIMO-OFDM systems and how to increase the capacity. It has been proved that the capacity of a MIMO system with space-dimensional water-filling power allocation is greater than that of the system with uniform power allocation. In MIMO-OFDM systems, there is an additional degree of freedom to allocate power with respect to MIMO systems: the OFDM sub-channels in frequency-domain. With the singular value decomposition (SVD) applied to the channel frequency response matrix, the two-dimensional water-filling power allocation algorithm for MIMO-OFDM systems is proposed based on the Lagrange method, and the corresponding capacity analysis formula is derived. Simulation results show that the capacity of a MIMO-OFDM system with the proposed two-dimensional water-filling power allocation is greater than that of the system with uniform power allocation and also greater than that of the system with the one-dimensional water-filling power allocation.

Block diagonalisation with adaptive resource allocation algorithm for multi-user MIMO-OFDM systems

The challenging issue in multi-user MIMO-OFDM system is to cancel multi-access interference (MAI) when different users share the same subcarrier. Also, the presence of MAI makes the resource allocation problem very complicated. Hence it is essential to find the optimal transmit and receive weight vectors, to reduce MAI and to adaptively assign resources to meet the quality of service (QoS) requirements. In this paper, block diagonalisation (BD) with waterfilling power allocation is considered and analysed their performance. This BD with waterfilling power allocation algorithm increases the system capacity with zero MAI. In order to have further increase in system performance, the proposed method considers rate adaptation scheme and margin adaptation scheme. In rate adaptation technique BD with power and subcarrier allocation is performed to maximise the system capacity. In margin adaptation technique BD with power and bit allocation is done to improve QoS of the system. The simulation results show that there is significant improvement in system performance also guaranteeing zero MAI.

Block diagonalisation with adaptive resource allocation algorithm for multi-user MIMO-OFDM systems

The challenging issue in multi-user MIMO-OFDM system is to cancel multi-access interference (MAI) when different users share the same subcarrier. Also, the presence of MAI makes the resource allocation problem very complicated. Hence it is essential to find the optimal transmit and receive weight vectors, to reduce MAI and to adaptively assign resources to meet the quality of service (QoS) requirements. In this paper, block diagonalisation (BD) with waterfilling power allocation is considered and analysed their performance. This BD with waterfilling power allocation algorithm increases the system capacity with zero MAI. In order to have further increase in system performance, the proposed method considers rate adaptation scheme and margin adaptation scheme. In rate adaptation technique BD with power and subcarrier allocation is performed to maximise the system capacity. In margin adaptation technique BD with power and bit allocation is done to improve QoS of the system. The simulation results show that th...

Convergence of Iterative Waterfilling Algorithm for Gaussian Interference Channels

Iterative waterfilling power allocation algorithm for Gaussian interference channels is investigated. The system is formulated as a non-cooperative game. Based on the measured interference powers, the users maximize their own throughput by iteratively adjusting their power allocations. The Nash equilib- rium in this game is a fixed point of such iterative algorithm. Both synchronous and asynchronous power update are considered. Some sufficient conditions under which the algorithm converges to the Nash equilibrium are derived.

Linear Water-Filling Power Allocation Algorithm in OFDMA System

Power allocation is an important issue of resource scheduling in OFDMA system. In this paper, an algorithm of linear water-filling power allocation is proposed through searching for a rapid means for confirming the sub-carriers which need not allocate power. It can finish the process of power water-filling without time after time iterative calculation. The simulation results show that the throughput of the proposed algorithm approaches the algorithm of iterated water-filling power allocation.