Wyniki wyszukiwania - Biblioteka Nauki

1

Pilot symbol error re-orthogonalization in 2×2 mimo systems of wireless communication

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Romanuke V.

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tom R. 61 nr 3 (222)

43--67

EN

A 2×2 MIMO wireless communication system with channel estimation is simulated, in which two transmit, and two receive antennas are employed. The orthogonal pilot signal approach is used for the channel estimation, where the Hadamard sequences are used for piloting. Data are modulated by coherent binary phase-shift keying, whereupon an orthogonal space-time block coding subsystem encodes information symbols by using the Alamouti code. Based on the simulation, it is ascertained a possibility to decrease the bit-error rate by substituting the Hadamard sequences for the sequences having irregular structures, and constituting the eight known orthogonal bases. Considering a de-orthogonalization caused by two any pilot sequence symbol errors, the bit-error rate is decreased by almost 2.9 %. If de-orthogonalizations are caused by two repeated indefinite, and definite pilot sequence symbol errors, the decrements are almost 16 % and 10 %, respectively. Whichever sequences are used for piloting, the 2×2 MIMO system is ascertained to be resistant to the de-orthogonalization if the frame is of 128 to 256 symbols piloted with 32 to 64 symbols, respectively.

PL

W pracy przedstawiono symulowany system komunikacji bezprzewodowej 2×2 MIMO z oszacowaniem kanału, składający się z dwóch anten nadawczych i dwóch anten odbiorczych. W procesie szacowania kanału zastosowano podejście ortogonalnego sygnału pilotującego z wykorzystaniem sekwencji Hadamarda. Na potrzeby badań symulacyjnych przyjęto modulowanie danych za pośrednictwem spójnego binarnego kluczowania z przesunięciem fazowym, podczas gdy ortogonalny podsystem kodowania bloków czasoprzestrzennych odpowiedzialny był za kodowanie informacji z wykorzystaniem kodu Alamouti. Na podstawie symulacji ustalono możliwość zmniejszenia współczynnika błędnych bitów przez zastąpienie sekwencji Hadamarda sekwencjami należącymi do ośmiu znanych baz ortogonalnych i charakteryzującymi się nieregularnymi strukturami. W przypadku deortogonalizacji wynikającej z dwóch dowolnych błędów symboli sekwencji pilotujących, współczynnik ten został zmniejszony o prawie 2.9 %. Jeśli deortogonalizacje są spowodowane przez dwa powtarzające się błędy symboli sekwencji pilotujących, nieokreślone i określone błędy uległy zmniejszeniu o odpowiednio 10 % i 16 %. Bez względu na to, które sekwencje zostały użyte do pilotowania, wykazano odporność systemu 2×2 MIMO na deortogonalizację w przypadku, gdy ramka zawierała od 128 do 256 symboli, a rozmiar sekwencji pilotującej mieścił się w zakresie od 32 do 64 symboli.

2

Traveling salesman problem parallelization by solving clustered subproblems

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Romanuke V.

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tom Vol. 48, No. 4

453--481

EN

A method of parallelizing the process of solving the traveling salesman problem is suggested, where the solver is a heuristic algorithm. The traveling salesman problem parallelization is fulfilled by clustering the nodes into a given number of groups. Every group (cluster) is an open-loop subproblem that can be solved independently of other subproblems. Then the solutions of the respective subproblems are aggregated into a closed loop route being an approximate solution to the initial traveling salesman problem. The clusters should be enumerated such that then the connection of two “neighboring” subproblems (with successive numbers) be as short as possible. For this, the destination nodes of the open-loop subproblems are selected farthest from the depot and closest to the starting node for the subsequent subproblem. The initial set of nodes can be clustered manually by covering them with a finite regular-polygon mesh having the required number of cells. The efficiency of the parallelization is increased by solving all the subproblems in parallel, but the problem should be at least of 1000 nodes or so. Then, having no more than a few hundred nodes in a cluster, the genetic algorithm is especially efficient by executing all the routine calculations during every iteration whose duration becomes shorter.

3

Zero-sum games on a product of staircase-function finite spaces

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Romanuke V.

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tom Vol. 44

75--91

EN

A tractable method of solving zero-sum games defined on a product of staircase-function finite spaces is presented. The method is based on stacking solutions of “smaller” matrix games, each defined on an interval where the pure strategy value is constant. The stack is always possible, even when only time is discrete, so the set of pure strategy possible values can be continuous. Any combination of the solutions of the “smaller” matrix games is a solution of the initial zero-sum game.

4

Acceptable-and-attractive Approximate Solution of a Continuous Non-Cooperative Game on a Product of Sinusoidal Strategy Functional Spaces

100%

Romanuke V.

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2021

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tom Vol. 46, No. 2

173--197

EN

A problem of solving a continuous noncooperative game is considered, where the player’s pure strategies are sinusoidal functions of time. In order to reduce issues of practical computability, certainty, and realizability, a method of solving the game approximately is presented. The method is based on mapping the product of the functional spaces into a hyperparallelepiped of the players’ phase lags. The hyperparallelepiped is then substituted with a hypercubic grid due to a uniform sampling. Thus, the initial game is mapped into a finite one, in which the players’ payoff matrices are hypercubic. The approximation is an iterative procedure. The number of intervals along the player’s phase lag is gradually increased, and the respective finite games are solved until an acceptable solution of the finite game becomes sufficiently close to the same-type solutions at the preceding iterations. The sufficient closeness implies that the player’s strategies at the succeeding iterations should be not farther from each other than at the preceding iterations. In a more feasible form, it implies that the respective distance polylines are required to be decreasing on average once they are smoothed with respective polynomials of degree 2, where the parabolas must be having positive coefficients at the squared variable.