Browsing by Subject "Discrete optimization"

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Open Access
Discrete-phase constant envelope precoding for massive MIMO systems
(Institute of Electrical and Electronics Engineers Inc., 2017) Kazemi, M.; Aghaeinia, H.; Duman, T. M.
We consider downlink of a multiuser massive multiple-input multiple-output (MIMO) system and focus on reducing the hardware costs by using a single common power amplifier and separate phase shifters (PSs) for antenna front-ends. In the previous literature, the use of analog PSs in this setup has been considered. Here, we study the use of practical digital PSs, which only support a limited set of discrete phases. Considering the sum of interference powers as a metric, we formulate the corresponding nonlinear discrete optimization problem and solve for the phases to be used during transmission. We devise a low-complexity algorithm, which employs a trellis structure providing suboptimal, but efficient and effective solutions. We demonstrate via examples that the proposed solutions have comparable performance to conventional analog PS-based algorithms. Furthermore, we prove that by utilizing discrete-phase constant envelope precoding, the interference can be made arbitrarily small by increasing the number of antennas. Therefore, the asymptotic gains promised by massive MIMO systems are preserved. We also obtain closed-form expressions for the rate loss due to errors in the phase and amplitude of the PSs, for both low and high SNR regimes.
Open Access
Optimization framework for simultaneous transmit and receive operations in wireless local area network
(2022-05) Bilaloğlu, Ege
Full duplex communication technology draws substantial interest among wireless network operators due to its ability to increase the network capacity through concurrent transmissions. Despite this advantage, interference issue caused by close distances between stations makes it challenging to integrate simultaneous transmit and receive mode into wireless networks. Motivated by the objective of minimal overhead in full duplex transmissions of access points, we provide an optimization framework to minimize the latest completion time of transmissions. In this problem, we aim to find an optimal schedule of transmissions that maximizes concurrent operations in order to reduce the makespan. We formulate the problem for both single and multiple concurrency assumptions separately. For single concurrency, we provide a mixed integer programming (MIP) model using scheduling based formulation along with a greedy heuristic. Modeling the problem as a matching problem between two disjoint sets of supplies and demands, we develop a linear programming (LP) model with a totally unimodular constraint matrix. We utilize Hopcroft-Karp algorithm for solving the resulting maximum cardinality bipartite matching problem. For multiple concurrency; we formulate a flow based integer programming model, demonstrate properties of the extreme points in its LP relaxation, develop valid inequalities and optimality cuts. As an extension, we add due dates for each station to complete their transmissions and formulate an MIP model and develop an algorithm for this variant. Additionally, we provide a proof for NP-completeness of minimum total tardiness problem with single concurrency. To evaluate the performance of the proposed formulations, we perform a range of computational experiments. Finally, we conduct sensitivity analyses to evaluate the effects of the parameters on the objective value and the solution times.