Water-filling Power Allocation 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.

Downlink Training Sequence Design Based on Waterfilling Solution for Low-Latency FDD Massive MIMO Communications Systems

Future generations of wireless communications systems are expected to evolve toward allowing massive ubiquitous connectivity and achieving ultra-reliable and low-latency communications (URLLC) with extremely high data rates. Massive multiple-input multiple-output (m-MIMO) is a crucial transmission technique to fulfill the demands of high data rates in the upcoming wireless systems. However, obtaining a downlink (DL) training sequence (TS) that is feasible for fast channel estimation, i.e., meeting the low-latency communications required by future generations of wireless systems, in m-MIMO with frequency-division-duplex (FDD) when users have different channel correlations is very challenging. Therefore, a low-complexity solution for designing the DL training sequences to maximize the achievable sum rate of FDD systems with limited channel coherence time (CCT) is proposed using a waterfilling power allocation method. This achievable sum rate maximization is achieved using sequences produced from a summation of the user’s covariance matrices and then applying a waterfilling power allocation method to the obtained low-complexity training sequence. The results show that the proposed TS outperforms the existing methods in the medium and high SNR regimes while reducing computational complexity. The obtained results signify the proposed TS’s feasibility for practical consideration compared with the existing DL training sequence designs.

Deployment and Robust Hybrid Beamforming for UAV MmWave Communications

We deploy an unmanned aerial vehicle (UAV) equipped with a large-scale uniform planar array (UPA) to serve multiple ground users in millimeter-wave band. Particularly, the practical UAV jitter is carefully considered, which may affect the beam gains and impact the communication quality. To provide a stable service, we first model the attitude change of the UPA caused by UAV jitter. Then, an optimization problem is formulated to maximize the minimum achievable rate of the users by optimizing the position and robust hybrid beamforming of the UAV. To solve the non-convex problem with highly coupled variables, a two-stage optimization strategy is developed. The first stage aims to decouple the beamforming from the original problem and design the UAV deployment under the assumption of an ideal beam pattern. The second stage aims to design robust hybrid beamforming with the obtained UAV position. Specifically, we first design analog beamforming for wide beams to cover the potential jitter angle range for each user via a chirp sequence-inspired method. Then, with equivalent channel estimation, we design digital beamforming by combining zero-forcing and water-filling power allocation algorithms. Extensive simulation results show the performance superiority of the proposed solution compared to the benchmark algorithms.

Proactive Eavesdropping of Physical Layer Security Aided Suspicious Communications in Fading Channels

Proactive eavesdropping is an effective approach to legitimately surveil the suspicious communications. Current studies all considered that physical layer security (PLS) techniques such as the wiretap coding are not applied by the suspicious users (SUs) to protect their communications. Contrary to that, we consider that the wiretap coding in PLS is adopted by the SUs to defend against the proactive eavesdropping from the legitimate monitor over fading channels. Under the fixed power allocation (FPA) and the water-filling power allocation (WFPA) at the SUs, the problem of jamming power allocation at the monitor to maximize the relative eavesdropping rate under the average transmit power constraint is investigated. The optimization problem is solved by two nested optimizations, where the bisection search method is used in the outer optimization, and the Lagrange duality method and the successive convex approximation method are used in the inner optimization. Simulation results confirm the effectiveness of the proposed algorithms compared to various baseline algorithms. It is shown that the proposed algorithm under the WFPA at the SUs outperforms the one under the FPA at the SUs, and the monitor achieves lower relative eavesdropping rate when the SUs adopt a stricter secure transmission scheme.

Hybrid Beamforming Design for Self-Interference Cancellation in Full-Duplex Millimeter-Wave MIMO Systems with Dynamic Subarrays.

Full-duplex (FD) millimeter-wave (mmWave) multiple-input multiple-output (MIMO) communication is a promising solution for the extremely high-throughput requirements in future cellular systems. The hybrid beamforming structure is preferable for its low hardware complexity and low power consumption with acceptable performance. In this paper, we introduce the hardware efficient dynamic subarrays to the FD mmWave MIMO systems and propose an effective hybrid beamforming design to cancel the self-interference (SI) in the considered system. First, assuming no SI, we obtain the optimal fully digital beamformers and combiners via the singular value decomposition of the uplink and downlink channels and the water-filling power allocation. Then, based on the obtained fully digital solutions, we get the dynamic analog solutions and digital solutions using the Kuhn-Munkres algorithm-aided dynamic hybrid beamforming design. Finally, we resort to the null space projection method to cancel the SI by projecting the obtained digital beamformer at the base station onto the null space of the equivalent SI channel. We further analyze the computational complexity of the proposed method. Numerical results demonstrate the superiority of the FD mmWave MIMO systems with the dynamic subarrays using the proposed method compared to the systems with the fixed subarrays and the half-duplex mmWave communications. When the number of RF chains is 6 and the signal-to-noise ratio is 10 dB, the proposed design outperforms the FD mmWave MIMO systems with fixed subarrays and the half-duplex mmWave communications, respectively, by 22.4% and 47.9% in spectral efficiency and 19.9% and 101% in energy efficiency.

Beamforming Optimization for Intelligent Reflecting Surface-Assisted MIMO Systems

To improve the spectral efficiency of symmetry-based intelligent reconfigurable surface (IRS)-assisted MIMO communication systems, this paper investigates the joint precoding and passive beamforming optimization problem for millimeter-wave point-to-point MIMO systems under both ideal and practical IRS phase shifts. For the ideal IRS phase shifts setup, we derive a simplified approximate spectral efficiency expression based on Jensen’s inequality and propose a minimum mean square error (MMSE)-based algorithm to transform the simplified non-convex problem into a solvable convex function. For the practical IRS phase shifts setup, we propose a multi-start stepwise optimization algorithm to obtain the passive beamforming by stepwise iterative search. Finally, with the above-obtained passive beamforming, the optimal precoding is derived by performing the singular value decomposition (SVD) on the effective channel and water-filling power allocation. The simulation results verify our performance analysis and demonstrate that spectral efficiency can be effectively improved compared to various benchmark schemes.

Two-Dimensional Power Allocation for Optical MIMO-OFDM Systems Over Low-Pass Channels

Multiple-input multiple-output (MIMO) combined with orthogonal frequency-division multiplexing (OFDM) technique can dramatically increase the achievable rate of visible light communication (VLC) systems. The channel in a VLC system with light-emitting diode (LED) luminaires is generally low-pass, which highly limits the achievable rate of practical VLC systems. This aspect has largely been ignored in the analysis for MIMO-OFDM VLC systems. As wide parts of the bandwidth at higher frequencies are severely attenuated, the choice of the power loading on every frequency bin has a large impact on the achieved bit rate. Thus, in this paper, we propose a two-dimensional water-filling (2D-WF) power allocation algorithm that operates both in frequency and space domains to efficiently improve the rate achieved by MIMO-OFDM VLC systems over low-pass VLC channels. The achievable rates and optimal bandwidths of a MIMO-OFDM VLC system are derived analytically using the proposed 2D-WF power allocation algorithm and five conventional power allocation strategies, including uniform (UF) power allocation, pre-emphasis (PE) power allocation, beamforming (BF) power allocation, and two kinds of one-dimensional water-filling (1D-WF) power allocation. Our simulation results show that the achievable rate of a MIMO-OFDM VLC system in a typical indoor environment can be significantly degraded by the low-pass effect. The proposed 2D-WF power allocation outperforms all other schemes in terms of achievable bit rate.

Attitude Information Aided Digital Beamforming in Millimeter-Wave MIMO Systems

Attitude information can be utilized for beam tracking in millimeter-wave (mmWave) analog beamforming. It provides the direction of arrival (DOA) information of the user equipment (UE) when it rotates, and thus, significantly reduces the overhead of beam searching. However, in digital beamforming (DBF), the transceivers are not designed based on DOAs, which makes it more challenging to utilize attitude information to reduce system overhead. In this article, we propose an attitude information aided DBF algorithm. Specifically, based on the clustered channel model, we derive the relationship between channel variation and the attitude of UE during the rotation. Furthermore, it is proved that only the transmitter at UE requires to be redesigned after the rotation, while the receiver at base station does not. Compared with the joint transceiver design, the performance loss is generally trivial. Therefore, we propose an AIA digital transmitter design algorithm for uplink transmission with equal power allocation. The spectral efficiency performance can approximate the optimal joint transceiver design performance without real-time channel state information. We also extend the method to unequal power allocation case and propose the algorithm with water-filling power allocation. Finally, simulation results are presented to examine the effectiveness of proposed algorithms.

Optimal Zero-Forcing Hybrid Downlink Precoding for Sum-Rate Maximization

This letter studies zero-forcing (ZF) hybrid precoding for maximizing the sum-rate of a downlink multi-user massive multi-input multi-output (mMIMO) system. Assuming the water-filling power allocation across different users, we derive the optimal digital precoder based on the Karush-Kuhn-Tucker (KKT) condition. We then formulate the optimization of the analog precoder as an unconstrained nonlinear problem, which can be efficiently solved by the conjugate gradient method. The resultant hybrid precoder is optimal in the sense that it uses no approximation to the objective function of sum-rate. Therefore, it outperforms the state-of-the-art methods as verified by the numerical simulations.

Borrowing Arrows With Thatched Boats: Exploiting The Reactive Primary Communications for Boosting Jamming-Assisted Proactive Eavesdropping

This paper investigates a cognitive information surveillance scenario, where a half-duplex legitimate monitor (E) aims to eavesdrop the frequency division multiple access based suspicious downlink broadcasting communication, which shares the same spectrum with a primary downlink broadcasting system. Specifically, the suspicious transmitter (ST) employs water-filling power allocation over all orthogonal frequency bands (FBs) to maximize the sum suspicious communication rate of all suspicious receivers (SRs), while the primary transmitter (PT) purposely maximizes the minimum communication rate among the primary receivers (PRs). Under this setup, E picks up certain FBs to jam and eavesdrops over the remaining FBs, and intends to control its transmit jamming beamforming over the jammed FBs to deliberately interfere with the corresponding PRs and SRs, such that the PT and the ST will reactively reallocate their power to facilitate E's eavesdropping. Our objective is to maximize the sum instantaneous (ergodic) eavesdropping rate at E, by jointly optimizing its jamming set and the corresponding jamming beamformers. The optimization problem is non-convex and its approximate and sub-optimal solutions are provided by some convex optimization procedures, along with the optimal and greedy jamming set selections. Results show the effectiveness of our proposed jamming-assisted eavesdropping compared to competitive benchmarks.

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.

Multi-user hybrid precoding for mmWave massive MIMO systems with sub-connected structure

Hybrid precoding achieves a compromise between the sum rate and hardware complexity of millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems. However, most prior works on multi-user hybrid precoding only consider the full-connected structure. In this paper, a novel multi-user hybrid precoding algorithm is proposed for the sub-connected structure. Based on the improved successive interference cancellation (SIC), the analog precoding matrix optimization problem is decomposed into multiple analog precoding sub-matrix optimization problems. Further, a near-optimal analog precoder is designed through factorizing the precoding sub-matrix for each sub-array. Furthermore, digital precoding is designed according to the block diagonalization (BD) technology. Finally, the water-filling power allocation method is used to further improve the communication quality. The extensive simulation results demonstrate that the sum rate of the proposed algorithm is higher than the existing hybrid precoding methods with the sub-connected structure, and has higher energy efficiency compared with existing approaches. Moreover, the proposed algorithm is closer to the state-of-the-art optimization approach with the full-connected structure. In addition, the simulation results also verify the effectiveness of the proposed hybrid precoding design of the uniform planar array (UPA).

Variable-Bandwidth Model and Capacity Analysis for Aerial Communications in the Terahertz Band

In this work, 0.75-10 THz band is explored for non-terrestrial communications, by leveraging the improved atmospheric conditions at various altitudes. A channel model for aerial communications at THz band is proposed to calculate the common flat bands for frequency-selective path gain and the colored noise spectrums, both of which are highly affected by the atmospheric conditions. With capacity computation based on common flat bands, we consider aerial vehicles at different altitudes and distances, under realistic weather and channel fading conditions, due to beam misalignment and also multi path fading. An extensive capacity analysis is presented, considering equal and water-filling power allocation. It is shown that, when there is no fading, capacity for aerial links is several orders of magnitude larger than the sea-level capacity. When ergodic capacity is computed for the fading scenarios, it is shown that the impact of fading vanishes with altitude. Sea-level ergodic capacity is increased by an order of magnitude for drone-to-drone communications, providing several Tbps at 10 m range, while 10s of Tbps is achievable among jet planes and UAVs, and several 100s of Tbps is possible for satellites/cubesats at 1 km under fading, suggesting that THz band is a promising alternative for aerial communications.

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.

Comparison of UCA-OAM and UCA-MIMO systems for sub-THz band line-of-sight spatial multiplexing transmission

This paper compares the uniform circular array based orbital angular momentum (UCA-OAM) scheme, which enables spatial multiplexing transmission of data symbols via multiple OAM modes, with the UCA-MIMO scheme through numerical analysis and simulation in terms of spectral efficiency and feedback over-head. Specifically, based on the relations between the eigenmodes of the UCA-SVD-MIMO system and the modes of UCA-OAM system as well as the capacity formula, the channel capacities of the two systems are compared for the cases where equal power allocation and waterfilling power allocation are employed, and then the effectiveness of the analytical results are verified through simulation.

UCA-Based OAM Non-Orthogonal Multi-Mode Multiplexing

Electromagnetic waves carrying orbital angular momentum (OAM) can improve the spectral efficiency of communication systems by multiplexing a number of OAM modes. However, since being not able to perform water-filling power allocation and adaptive modulation for each sub-channel like closed-loop multiple-input multiple-output (MIMO) systems, the traditional orthogonal multi-mode OAM multiplexing system usually has poor bit error rate (BER) performance due to the inherent large divergence angle of high-order orthogonal OAM beams. Therefore, in this article we propose a non-orthogonal OAM (NO-OAM) multi-mode multiplexing scheme based on uniform circular array (UCA), which regulates the divergence angles of all non-orthogonal OAM beams to be the same, circumventing the problem that large beam divergence of high-order orthogonal OAM modes results in low received signal-to-noise ratio (SNR) at the receive UCA with a fixed aperture. Mathematical analysis and numerical simulations show that in contrast to the existing uniform concentric circular array (UCCA) beam adjustment scheme, the proposed NO-OAM scheme has slightly better beam adjustment effect but with only one UCA. Moreover, in contrast to the traditional orthogonal OAM multi-mode transmission, the proposed NO-OAM multi-mode multiplexing scheme has asymptotically equivalent channel capacity and much lower BER.

Linear Water-Filling Power Allocation Method in Wireless MIMO Ultraviolet Communication

Linear Water-Filling Power Allocation Method in Wireless MIMO Ultraviolet Communication

Block diagonalization precoding and power allocation for clustering small-cell networks

The clustering network is a solution to improve data-rate transmission in small-cells. In this case, clustering small-cells (CSCs) adopt a multiple antennas concept. The multiple antennas are used to maximize the downlink data-rate transmission at the users, but it requires precoding techniques to minimize interference among CSC users. This paper proposes a block diagonalization (BD) as a precoding technique for minimizing interference among CSC users. The performance of the BD precoding implemented on the clustering network under various numbers of small-cells. The CSC also implements a water-filling power allocation (PA-CoopWF) to distribute the available transmission power along with the CSCs antennas. To show the performance, our paper simulates two types of precoding techniques; those are the proposed BD and minimum mean square error (MMSE) in CSCs. Based on the receiver user parts under the overlapping coordination of CSCs, our method based on the BD precoding achieves considerably higher data-rate transmission compared to the MMSE precoding, especially on larger clusters. The simulation also shows that by implementing CSC with the BD in short-range distances and higher numbers of antennas, it promotes better data-rate performances compared to the MMSE precoding by 2.75 times at distance 100m and 67% at 50 antennas.

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.

Energy efficient power control for device to device communication in 5G networks

Next generation cellular networks require high capacity, enhanced energy efficiency and guaranteed quality of service (QoS). In order to meet these targets, device-to device (D2D) communication is being considered for future 5th generation especially for certain applications that require the proximity gain, the reuse gain, and the hop gain. In this paper, we investigate energy efficient power control for the uplink of an OFDMA (orthogonal frequency-division multiple access) single-cell communication system composed of both regular cellular users and device to device (D2D) pairs. Firstly, we analyze and mathematically model the actual requirements forD2D communications and traditional cellular links in terms of minimum rate and maximum power requirement. Secondly, we use fractional programming in order to transform the original problem into an equivalent concave one and we use the non-cooperative Game theory in order to characterize the equilibrium. Then, the solution of the game is given as a water-filling power allocation. Furthermore, we implement a distributed power allocation scheme using three ways: a) Fractional programming techniques b) Closed form expression (the novelty is the use of wright omega function). c) Inverse water filling. Finally, simulations in both static and dynamic channel setting are presented to illustrate the improved performance in term of EE, SE (spectral efficiency) and time of execution of the iterative algorithm (Dinkelbach) than the closed form algorithms.