652 research outputs found
Widely linear processing improves the throughput of nonorthogonal user access
No full textThe quality-of-service (QoS) provided by wireless communication networks can be upgraded by the technique of non-orthogonal multiple-access (NOMA) in tandem with widely linear beamforming (WLB), which uses a pair of beamformers for each information symbol. Conventionally, rate-fairness among the users is achieved by maximizing the users’ minimal throughput (max-min throughput optimization). However, this is computationally challenging, as each iteration requires solving a high-dimensional convex optimization problem, even for small networks. We circumvent this by maximizing the geometric mean (GM) of the users’ throughput (GM-throughput maximization) and design novel algorithms based on iterating closed-form expressions are developed, which are shown to be hundreds of times more computationally efficient than the existing algorithms that are based on convex-solvers. The proposed algorithms are developed for both conventional wireless networks and networks requiring ultra-reliable and low-latency communications (URLLC)
Regularized zero-forcing aided hybrid beamforming for millimeter-wave multi-user MIMO systems
No full textThis paper considers hybrid beamforming consisting of analog beamforming (ABF) coupled with digital baseband beamforming (DBF) which is designed for multi-user (MU) multiple input multiple output (MIMO) millimeter-wave (mmWave) communications. ABF uses a limited number of radio frequency (RF) chains and finite-resolution phase-shifters to alleviate the power consumption at the base station (BS), while DBF uses either zero-forcing beamforming (ZFB) or regularized zero forcing beamforming (RZFB) to restrain MU interference. The joint design of ABF and DBF constitutes a computationally challenging mixed discrete continuous optimization problem. The paper develops efficient algorithms for its solution, which iterate scalable-complex expressions. Furthermore, we conceive a new class of MU RZFB for attaining higher rates. Simulations are provided to demonstrate the viability of the proposed algorithms and the advantages of the conceived RZFB
Active RIS-Assisted Multi-User Multi-Stream Transmit Precoding Relying on Scalable-Complexity Iterations
No full textThis is the first investigation focused on delivering multi-stream information to multiple multi-antenna users employing an active reconfigurable intelligent surface (aRIS)-assisted system. We conceive the joint design of the transmit precoders and of the aRIS’s power-amplified reconfigurable elements (APRES) to enhance the log-det rate objective functions for all users, which poses large-scale mixed discrete continuous problems. We develop a max-min log-det solver, which iterates quadratic-solvers of cubic complexity to maximize the nonsmooth function representing the minimum of the users’ log-det rate functions. To mitigate the computational burden associated with cubically escalating complexity in large-scale scenarios, we introduce a pair of alternative problems aimed at maximizing the smooth functions representing the sum of the users’ log-det rate function (sum log-det) and the soft minimum of the users’ log-det rate function (soft min log-det). We develop sum log-det and soft max-min solvers, leveraging closed-form expressions of scalable (linear) complexity for efficient computation. This approach ensures practicality in addressing large-scale scenarios. Furthermore, the soft min log-det enables us to enhance the log-det rates for all users and their sum, ultimately improving the quality of delivering multi-user multi-stream information
Holographic multi-user multi-stream beamforming maintaining rate-fairness
No full textWe present the first investigation into the transmission of multi-stream information from a base station equipped with reconfigurable holographic surfaces (RHS) to multiple users with the aid of multi-antenna arrays. Building upon this, we propose the joint design of RHS and baseband beamformers that enables multi-stream delivery at fair rates across all users. Specifically, we first introduce a max-min rate optimization approach, which aims for maximizing the minimum rate for all users through iterative solutions of quadratic problems. To reduce complexity, we then propose a surrogate-based optimization approach that offers a low-complexity design alternative relying on closed-form updates. Our simulations show that the surrogate-based approach achieves nearly the same minimum rate as max-min optimization, while delivering sum-rates comparable to those of sum-rate maximization, overcoming the rate-fairness deficiency typical of the latter
Active-RIS enhances the multi-user rate of multi-carrier communications
No full textThis paper explores a multi-user multi-carrier system leveraging an active reconfigurable intelligent surface (RIS), where the joint design of the RIS’s programmable reflecting elements and the subcarrier-wise beamformers at the base station is investigated. To overcome the limitation of the conventional design, which aims solely at sum-rate maximization resulting in zero rates for some users across all sub-carriers and thus failing to boost all users rates, we propose the two alternative designs: one maximizing the geometric mean of the users’ rates (GM-rate maximization) and the other maximizing the soft users’ minimum rate (soft max-min rate optimization). However, they pose challenges as large-scale nonconvex problems, rendering convex-solver computational approaches impractical. To tackle this, we develop iterative computational procedures based on closed-form expressions of scalable complexity. Extensive simulations demonstrate the substantial benefits of these novel designs in significantly enhancing multi-user rates. Notably, under the same power budget, the active-RIS-assisted multi-carrier system achieves approximately twice the minimum user-rate or sum rate compared to RIS-less or passive-RIS-assisted counterparts
Max-min rate optimization of low-complexity hybrid multi-user beamforming maintaining rate-fairness
No full textA wireless network serving multiple users in the millimeter-wave or the sub-terahertz band by a base station is considered. High-throughput multi-user hybrid-transmit beamforming is conceived by maximizing the minimum rate of the users. For the sake of energy-efficient signal transmission, the array-of-subarrays structure is used for analog beamforming relying on low-resolution phase shifters. We develop a convexsolver based algorithm, which iteratively invokes a convex problem of the same beamformer size for its solution. We then introduce the soft max-min rate objective function and develop a scalable algorithm for its optimization. Our simulation results demonstrate the striking fact that soft max-min rate optimization not only approaches the minimum user rate obtained by max-min rate optimization but it also achieves a sum rate similar to that of sum-rate maximization. Thus, the soft max-min rate optimization based beamforming design conceived offers a new technique of simultaneously achieving a high individual quality-of-service for all users and a high total network throughput
Finite-blocklength RIS-aided transmit beamforming
No full textThis paper considers the downlink of an ultra-reliable low-latency communication (URLLC) system in which a base station (BS) serves multiple single-antenna users in the short (finite) blocklength (FBL) regime with the assistance of a reconfigurable intelligent surface (RIS). In the FBL regime, the users' achievable rates are complex functions of the beamforming vectors and of the RIS's programmable reflecting elements (PREs). We propose the joint design of the transmit beamformers and PREs to maximize the geometric mean (GM) of these rates (GM-rate) and show that this approach provides fair rate distribution and thus reliable links to all users. A novel computational algorithm is developed, which is based on closed forms to generate improved feasible points. Simulations show the merit of our solution.</p
A new class of analog precoding for multi-antenna multi-user communications over high-frequency bands
No full textA network relying on a large antenna-array-aided base station is designed for delivering multiple information streams to multi-antenna users over high-frequency bands such as the millimeter-wave and sub-Terahertz bands. The state-of-the-art analog precoder (AP) dissipates excessive circuit power due to its reliance on a large number of phase shifters. To mitigate the power consumption, we propose a novel AP relying on a controlled number of phase shifters. Within this new AP framework, we design a hybrid precoder (HP) for maximizing the users’ minimum throughput, which poses a computationally challenging problem of large-scale, nonsmooth mixed discrete-continuous log-determinant optimization. To tackle this challenge, we develop an algorithm which iterates through solving convex problems to generate a sequence of HPs that converges to the max-min solution. We also introduce a new framework of smooth optimization termed soft max-min throughput optimization. Additionally, we develop another algorithm, which iterates by evaluating closed-form expressions to generate a sequence of HPs that converges to the soft max-min solution. Simulation results reveal that the HP soft max-min solution approaches the Pareto-optimal solution constructed for simultaneously optimizing both the minimum throughput and sum-throughput. Explicitly, it achieves a minimum throughput similar to directly maximizing the users’ minimum throughput and it also attains a sum-throughput similar to directly maximizing the sum-throughput
Identification of impulsive interference channels
No full textIn this work, the problem of optimum and near-optimum identification of the parameters of the Middleton Class A impulsive interference model is considered. In particular, under the assumption of the availability of a set of independent samples from the Class A envelope distribution, the problems of basic batch estimation of the Class A parameters, recursive identification of the parameters, and efficient estimation of the parameters for small sample sizes, are investigated. Within the context of basic batch estimation, several estimators of the parameters are proposed and their asymptotic performances explored. From this analysis, estimates based on the method of moments are seen to be consistent and computationally desirable but highly inefficient, whereas more efficient likelihood-based estimators are seen to be computationally unwieldy. However, an estimator that initiates likelihood iteration with the method-of-moments estimates is seen to overcome these difficulties in its asymptotic performance. Unfortunately, simulation of this third estimator for moderate sample sizes reveals poor performance under these conditions. To overcome this lack of moderate-sample-size efficiency, a similar estimator that initiates likelihood iteration with physically motivated (but nonoptimal) estimates is also proposed. Simulation of this latter estimator for moderate sample sizes indicates that near-optimal performance is obtained by this technique. Within the context of recursive estimation, a recursive decision-directed estimator for on-line identification of the parameters of the Class A model is proposed. This estimator is based on an adaptive, Bayesian classification of each of a sequence of Class A envelope samples as either an impulsive sample or as a background sample. The performance characteristics of this algorithm are investigated, and an appropriately modified version is found to yield a global, recursive estimator of the parameters that performs very well for all parameter vectors in the parameter set of interest. Within the context of efficient estimation for small sample sizes, an algorithm that has the potential of providing efficient estimates of the Class A parameters for small sample sizes is proposed. For the single-parameter estimation problem, it is shown that the sequence of estimates obtained via this algorithm converges, and a characterization of the point to which the sequence converges is given. For both the single-parameter and two-parameter estimation problems, it is also seen, via an extensive simulation study, that the proposed estimator yields excellent estimates of the parameters for small sample sizes. It is anticipated that the results of this research will have widespread impact in the areas of communication, radar, and sonar due to the common occurrence of impulsive noise channels in these systems.Made available in DSpace on 2011-05-07T12:37:13Z (GMT). No. of bitstreams: 2
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