Scheduling Algorithm with Power Allocation for Random Unitary Beamforming

Random unitary beamforming is one of the schemes that can reduce the amount of feedback information in multiuser diversity techniques with multiple-antenna downlink transmission. In Multiple-Input Multiple-Output (MIMO) systems, throughput performance is greatly improved using AMC (Adaptive Modulation and Coding). Throughput performance is also improved by allocating power among streams appropriately. In random unitary beamforming, the transmitter has only partial channel state information (CSI) of each receiver. Thus, it is difficult for random unitary beamforming to use conventional power allocation methods that assumes that all receivers has full CSI. In this paper, we propose a new scheduling algorithm with power allocation for downlink random unitary beamforming that improves throughput performance without full CSI. We provide numerical results of the proposed scheduling algorithm and compare them to those of the conventional random unitary beamforming scheduling algorithm. We show that random unitary beamforming achieves the best system throughput performance with two transmit antennas. We also show that the proposed algorithm attains higher throughput with the small increase of feedback than the random unitary beamforming scheduling algorithm.

In this paper, we consider the downlink transmission over a single-cell massive multiple-input-multiple-output (MIMO) system in the presence of multiple single-antenna eavesdroppers (massive MIMOME). We concentrate on the practical scenario where partial channel state information (CSI) of legitimate users and no CSI of eavesdroppers are available at the base station and consider both types of eavesdroppers including the non-colluding and colluding eavesdroppers. Random unitary beamforming (RUB) based scheme is used to describe the partial CSI of legitimate users. We derive the closed-form expression of ergodic secrecy rate for RUB based massive MIMOME transmission, and its single legitimate user particular case. We also present numerical results to illustrate the performance-complexity tradeoff among different massive MIMO transmission schemes. We show that RUB based scheme can enhance secrecy performance of massive MIMO transmission with lower implementation complexity.

Random unitary beamforming (RUB) is a multiple antenna transmission scheme requiring limited channel state information (CSI) with low computational complexity. In this paper, we investigate the security performance of RUB over a multiple-input single-output single-eavesdropper (MISOSE) broadcast channel. We derive the closed-form expressions of ergodic secrecy rate and the secrecy outage probability (SOP) of the resulting design. Meanwhile, the effect of artificial noise (AN) on physical layer (PHY) security performance of RUB-based MISOSE transmission is also investigated. Numerical results are presented to illustrate the tradeoff between performance and complexity of the proposed PHY security design. We show that the deployment of RUB offers an attractive solution for enhancing the security of wireless transmission systems.

In this letter, energy-efficient transmission and power allocation for fixed-gain amplify-and-forward relay networks with partial channel state information (CSI) are studied. In the energy-efficiency problem, the total power consumed is minimized while keeping the signal-to-noise-ratio (SNR) above a certain threshold. In the dual problem of power allocation, the end-to-end SNR is maximized under individual and global power constraints. Closed-form expressions for the optimal source and relay powers and the Lagrangian multiplier are obtained. Numerical results show that the optimal power allocation with partial CSI provides comparable performance as optimal power allocation with full CSI at low SNR.

Random unitary beamforming (RUB) can reduce the implementation complexity of massive multiple- input singleoutput (MIMO) downlink transmission by only requiring partial channel state information (CSI) at the transmitter. In this paper, we investigate the secrecy performance of a single- cell massive MIMO system with RUB in the presence of multiple noncolluding eavesdroppers. Specifically, we derive the closed-form expressions of the secrecy outage probability (SOP) for a massive MIMO transmission and its single legitimate user case. Numerical results are presented to illustrate the performance-complexity tradeoff among RUB based, zero-forcing (ZF) beamforming based, and maximum ratio transmission (MRT) based massive MIMO transmission schemes. We show that RUB based scheme can enhance secrecy performance of massive MIMO transmission with lower implementation complexity.

This paper studies power allocation for performance constrained dual-hop variable-gain amplify-and-forward (AF) relay networks in Nakagami- m fading. In this context, the performance constraint is formulated as a constraint on the end-to-end signal-to-noise-ratio (SNR) and the overall power consumed is minimized while maintaining this constraint. This problem is considered under two different assumptions of the available channel state information (CSI) at the relays, namely full CSI at the relays and partial CSI at the relays. In addition to the power minimization problem, we also consider the end-to-end SNR maximization problem under a total power constraint for the partial CSI case. We provide closed-form solutions for all the problems which are easy to implement except in two cases, namely selective relaying with partial CSI for power minimization and SNR maximization, where we give the solution in the form of a one-variable equation which can be solved efficiently. Numerical results are then provided to characterize the performance of the proposed power allocation algorithms considering the effects of channel parameters and CSI availability.

Multiple Input Multiple Output(MIMO) has been in much importance in recent past because of high capacity gain over a single antenna system. In this article, analysis over the capacity of the MIMO channel systems with spatial channel with modified precoder and decoder has been considered when the channel state information (CSI) is considered partial. Due to delay in acquiring transmitted information at the receiver end, the time selective fading wireless channel often induces incomplete or partial CSI. The dynamic CSI model has also been implemented consisting channel mean and covariance which leads to extracting of channel estimates and error covariance which then further applied with the modified precoder and decoder utilizing both the parameters indicating the CSI quality since these are the functions of temporal correlation factor, and based on this, the model covers data from perfect to statistical CSI, either partially or fully blind. It is found that in case of partial and imperfect CSI, the capacity depends on the statistical properties of the error in the CSI which has been manipulated according to the precoder and decoder conditions. Based on the knowledge of statistical distribution of the deviations in CSI knowledge, a new approach which maximizes the capacity of spatial channel model with modified precoder and decoder has been tried. The interference then interactively reduced by employing the iterative channel estimation and data detection approach, where by utilizing the detected symbols from the previous iteration, multiuser/MIMO channel estimation and symbol detection is improved.

This paper presents a new framework for designing decentralized rank-1 pre-coders in MIMO interference channel. The proposed pre-coders aim to separate the received signal points corresponding to different bits into distinct clusters at every receiver. This is accomplished by minimizing the overlaps between conditional probability density functions (PDFs) given the sent bits, which is shown to be equivalent to maximizing the weighted Euclidean distance between the signal points. This formulation is shown to be synonymous to minimizing an upper bound to the probability of error or maximizing the approximated Bhattacharya distances of the conditional PDFs. When full channel state information (CSI) is given at all transmitters and receivers, our design is shown to offer significant performance gain over a wide range of SNR when compared to other pre-coder designs in the literature. We also extend our pre-coder design to the case when transmitters only have partial CSI in an arbitrary form. When the partial CSI is given in the form of quantized levels of channel coefficients, our design is shown to retain considerable performance gain as we partition the channel coefficients with finer resolutions.

Wireless amplify-and-forward relay networks in which the source communicates with the relays and destination in the first phase and the relays forward signals to the destination in the second phase over orthogonal and uncorrelated Rayleigh fading channels are considered. Convex programming is used to obtain optimal and approximately optimal power allocation schemes to maximize the average signal-to-noise ratios at the output of the receiver filters under two different assumptions of <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">partial</i> channel state information (CSI). Analysis and simulation results demonstrate the superiority of the proposed power allocation schemes over the equal-power allocation scheme. Performance comparison to the extreme cases of i) direct transmission between the source and destination and ii) having full CSI is made to illustrate the gain and loss, respectively, of the proposed schemes. The impact of power allocation between the source and relays is also investigated by computer simulation.

In a wireless multi-user system using multiple antennas, full multiplexing gain can be achieved through perfect channel state information (CSI) at the base station (BS). However, because of the limitations on the feedback rate and of standard requirements, such as the 3GPP, it is difficult to obtain perfect CSI, or even partial CSI with the extremely large number of feedback bits needed at the region of high signal-to-noise ratios (SNR) in practical systems. Instead of a feedback channel resource, this paper considers another resource for the system, a cooperation channel, which can be used by users to participate in cooperation in a broadcast fading channel. The cooperation among users in a multi-user system has the effect of transforming it into a cooperative point-to-point MIMO system. This paper analyzes the cooperation channel gain and the mobile power used in a cooperation channel to maintain a constant rate gap against the zero-forcing beamforming scheme with full CSI at the BS. In addition, the performance results of this proposed cooperation strategy are provided by computer simulations.

This paper investigates the simultaneous wireless information and power transfer (SWIPT)-enabled cooperative non-orthogonal multiple access (NOMA) with full-duplex (FD) relaying. Two optimization problems are formulated to minimize the required transmit power with both full channel state information (CSI) and partial CSI (i.e., channel distribution information (CDI)). As both problems are non-convex without explicit solution methods, the semidefinite relaxation (SDR) is applied to relax them firstly. Then, for the full CSI case, a bilevel programming (BLP)-based method is presented to find the global optimal solution, and as an alternative, a successive convex approximation (SCA)-based method with arithmetic and geometric means (AGM) inequality is designed to achieve the suboptimal solution with low complexity. Moreover, in a special case with single transmit antenna, the closed-form expression of the optimal power allocation is derived for a given power splitting (PS) ratio and then the global optimal solution is found by using Bisection method. For the CDI case, the first-order Taylor expansion is adopted to approximate the non-convex constraints and then a SCA-based algorithm is designed to find the suboptimal solution. Numerical results validate our obtained theoretical results and proposed solution methods, and also show that by migrating FD relaying into SWIPT-enabled cooperative NOMA, a considerable system performance gain can be achieved for both full CSI and CDI cases. Besides, we also discuss the gain brought by NOMA and FD separately and the effect of the relay location on the system performance. It shows that FD may bring more contribution to the system performance improvement than NOMA.

Considering that wireless unidirectional full-duplex (FD) transmission is one of the FD transmissions over 5G mobile wireless networks, this paper proposes a joint receive and transmit relay beamformer design for systems consisting of a source, a FD relay, an intended destination, and an eavesdropper. The source and destination are single-antenna nodes, whereas the FD relay is a multi-antenna node. Assuming that full channel state information (CSI) is available and the eavesdropper processes two blocks of received data at a time, the joint optimization problem is reformulated as a semidefinite relaxation (SDR) problem (in terms of relay transmit beamformer), which is tight in the sense that the rank-one beamformer can always be recovered from the SDR solution. In order to significantly minimize the computational cost of the SDR implementation, a novel semi-analytical approach based on dual optimization is proposed to obtain the optimum transmit beamformer. When the number of data blocks is arbitrary, we propose a successive convex approximation approach for solving the original non-convex optimization problem and show that a stationary solution can be efficiently obtained. We then propose a distributionally robust beamformer design for the case of an arbitrary number of blocks, assuming that the means and covariance matrices of the eavesdropper's channels are known. Computer simulations show that the proposed semi-analytical solution matches with that obtained from numerical optimization of the SDR problem, the FD scheme significantly outperforms its half-duplex counterpart, and the proposed robust design provides robustness against CSI uncertainty.

We consider a wireless base station serving L users through L time-varying channels. It is well known that opportunistic scheduling algorithms with full channel state information (CSI) can stabilize the system and achieve the full capacity region. However, opportunistic scheduling algorithms with full CSI may not be energy efficient when the cost of channel acquisition is high and traffic rates are low. In particular, under the low traffic rate regime, it may be sufficient and more energy-efficient to transmit data with no CSI, i.e., to transmit data blindly, since no power for channel acquisition is consumed. In general, we show that purely channel-aware or purely channel-blind strategies are not necessarily optimal, and we must consider mixed strategies. We derive a unified scheduling algorithm that dynamically chooses to transmit data with full or no CSI based on queue backlog and channel statistics. Through Lyapunov analysis, we show that the unified algorithm can stabilize the downlink with optimal power consumption.

Random unitary beamforming (RUB) is an attractive low-complexity transmission scheme for multiuser MIMO broadcast channel. When there are a moderate number of users in the system, the sum rate performance of this signaling scheme becomes mainly interference-limited over high signal-to-noise ratio (SNR) region. In this paper, we study the performance of RUB-based multiuser MIMO systems when optimum combining is employed at mulitple-antenna mobile receivers to suppress multiuser interference. We adopt a geometric approach to derive the statistics of the output signal-to-interference ratio (SIR) of the optimum combiner, based on which a sum rate upper bound is obtained over high SNR region. We show through selected numerical examples that the proposed RUB with optimal combining achieves much better sum rate performance while maintaining low feedback load.

Random unitary beamforming (RUB) is an attractive transmission scheme for MIMO broadcast channels because of its ability to achieve high sum-rate capacity with limited feedback. In this letter, we derive the exact analytical expressions for the ergodic sum rate of MIMO broadcast channels with RUB. The analysis is facilitated by the development of the complete statistical characterization of ordered beam SINRs for a user, which can find their application in many related problems.