93 research outputs found
Optimum Transmission Through the Multiple-Antenna Gaussian Multiple Access Channel
"(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works."[EN] This paper studies the optimal points in the capacity region of Gaussian multiple access channels (GMACs) with constant fading, multiple antennas, and various power constraints. The points of interest maximize general rate objectives that arise in practical communication scenarios. Achieving these points constitutes the task of jointly optimizing the timesharing parameters, the input covariance matrices, and the order of decoding used by the successive interference cancellation receiver. To approach this problem, Carathéodory s theorem is invoked to represent time-sharing and decoding orders jointly as a finite-dimensional matrix variable. This variable enables us to use variational inequalities to extend results pertaining to problems with linear rate objectives to more general, potentially nonconvex, problems, and to obtain a necessary and sufficient condition for the optimality of the transmission parameters in a wide range of problems. Using the insights gained from this condition, we develop and analyze the convergence of an algorithm for solving, otherwise daunting, GMAC-based optimization problems.D. Calabuig was supported by Marie Curie International Outgoing Fellowship within the European Commission, Research Executive Agency, through the COMIC Project under Grant 253990. R. H. Gohary and H. Yanikomeroglu were supported in part by Huawei Canada Company, Ltd., and in part by the Ontario Ministry of Economic Development and Innovations within the Ontario Research Fund through the Research Excellence Program. This paper was presented at the 2013 IEEE International Symposium on Information Theory and the 2014 IEEE International Workshop on Signal Processing Advances in Wireless Communications.Calabuig Soler, D.; Gohary, RH.; Yanikomeroglu, H. (2016). Optimum Transmission Through the Multiple-Antenna Gaussian Multiple Access Channel. IEEE Transactions on Information Theory. 62(1):230-243. https://doi.org/10.1109/TIT.2015.2502244S23024362
Optimal Power Assignment for MIMO Channels Under Joint Total and Per-Group Power Constraints
In this paper we consider a communication system with one transmitter and one
receiver. The transmit antennas are partitioned into disjoint groups, and each
group must satisfy an average power constraint in addition to the standard
overall one. The optimal power allocation (OPA) for the transmit antennas is
obtained for the following cases: (i) fixed multiple-input multiple-output
(MIMO) orthogonal channel, (ii) i.i.d. fading MIMO orthogonal channel, and
(iii) i.i.d. Rayleigh fading multiple-input single-output (MISO) and MIMO
channels. The channel orthogonality is encountered in the practical case of the
massive MIMO channel under favorable propagation conditions. The closed-form
solution to the OPA for a fixed channel is found using the Karush-Kuhn-Tucker
(KKT) conditions and it is similar to the standard water-filling procedure
while the effect of the per-group average power constraint is added. For a
fading channel, an algorithm is proposed to give the OPA, and the algorithm's
convergence is proved via a majorization inequality and a Schur-concavity
property
Hierarchical coherent and non-coherent communication
[abstract not available]https://fount.aucegypt.edu/faculty_book_chapters/1213/thumbnail.jp
Optimization of Discrete Power and Resource Block Allocation for Achieving Maximum Energy Efficiency in OFDMA Networks
Most of the resource allocation literature on the energy-efficient orthogonal frequency division multiple access (OFDMA)-based wireless communication systems assume continuous power allocation/control, while, in practice, the power levels are discrete (such as in 3GPP LTE). This convenient continuous power assumption has mainly been due to either the limitations of the used optimization tools and/or the high computational complexity involved in addressing the more realistic discrete power allocation/control. In this paper, we introduce a new optimization framework to maximize the energy efficiency of the downlink transmission of cellular OFDMA networks subject to power budget and quality-of-service constraints, while considering discrete power and resource blocks (RBs) allocations. The proposed framework consists of two parts: 1) we model the predefined discrete power levels and RBs allocations by a single binary variable and 2) we propose a close-to-optimal semidefinite relaxation algorithm with Gaussian randomization to efficiently solve this non-convex combinatorial optimization problem with polynomial time complexity. We notice that a small number of power levels suffice to approach the energy efficiency performance of the continuous power allocation. Based on this observation, we propose an iterative suboptimal heuristic to further reduce the computational complexity. Simulation results show the effectiveness of the proposed schemes in maximizing the energy efficiency, while considering the practical discrete power levels
Optimization of a class of non-convex objectives on the Gaussian MIMO multiple access channel: Algorithm development and convergence analysis
In this paper we develop an algorithm for computing the optimal transmission parameters, which include the transmission covariance, the time-shares and the user-orderings that minimize a particular class of objectives defined over the capacity region of Gaussian multiple antenna multiple access channels. This class includes objectives that are twice-differentiable, non-increasing and convex in the users' rates, but not necessarily convex in the aforementioned transmission par
Conjoint Routing and Resource Allocation in OFDMA-based D2D Wireless Networks
In this paper, we develop a highly efficient twotier technique for jointly optimizing the routes, the subcarrier schedules, th
Polar Code Design for Irregular Multidimensional Constellations
Polar codes, ever since their introduction, have been shown to be very effective for various wireless communication channels. This, together with their relatively low implementation complexity, has made them an attractive coding scheme for wireless communications. Polar codes have been extensively studied for use with binary-input symmetric memoryless channels but little is known about their effectiveness in other channels. In this paper, a novel methodology for designing multilevel polar codes that works effectively with arbitrary multidimensional constellations is presented. In order for this multilevel design to function, a novel set merging algorithm, able to label such constellations, is proposed.We then compare the error rate performance of our design with that of existing schemes and show that we were able to obtain unprecedented results in many cases over the previously known best techniques at relatively low decoding complexity
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