Emolehmien ruokintakertojen vähentäminen ei tuo suuria säästöjä

Emolehmillä ruokintakertoja vähentämällä pyritään säästämään työkustannuksia ja siten parantamaan tuotannon taloudellista tulosta. Tutkittujen työmenekkien perusteella emolehmien ruokinta joka kolmas päivä pienensi kokonaistyökustannusta noin viidenneksen verrattuna päivittäiseen ruokintaan. Saavutetut säästöt eivät vaikuta kovin paljon emolehmätilan taloudelliseen kokonaistulokseen, mutta harvennetun ruokinnan tarjoamat muut edut voivat olla kustannussäästöjä oleellisempia.vo

Energy-Efficient Coordinated Multi-Cell Multigroup Multicast Beamforming with Antenna Selection

This paper studies energy-efficient coordinated beamforming in multi-cell multi-user multigroup multicast multiple-input single-output systems. We aim at maximizing the network energy efficiency by taking into account the fact that some of the radio frequency chains can be switched off in order to save power. We consider the antenna specific maximum power constraints to avoid non-linear distortion in power amplifiers and user-specific quality of service (QoS) constraints to guarantee a certain QoS levels. We first introduce binary antenna selection variables and use the perspective formulation to model the relation between them and the beamformers. Subsequently, we propose a new formulation which reduces the feasible set of the continuous relaxation, resulting in better performance compared to the original perspective formulation based problem. However, the resulting optimization problem is a mixed-Boolean non-convex fractional program, which is difficult to solve. We follow the standard continuous relaxation of the binary antenna selection variables, and then reformulate the problem such that it is amendable to successive convex approximation. Thereby, solving the continuous relaxation mostly results in near-binary solution. To recover the binary variables from the continuous relaxation, we switch off all the antennas for which the continuous values are smaller than a small threshold. Numerical results illustrate the superior convergence result and significant achievable gains in terms of energy efficiency with the proposed algorithm.Comment: 6 pages, 5 figures, accepted to IEEE ICC 2017 - International Workshop on 5G RAN Desig

A Customized Lattice Reduction Multiprocessor for MIMO Detection

Lattice reduction (LR) is a preprocessing technique for multiple-input multiple-output (MIMO) symbol detection to achieve better bit error-rate (BER) performance. In this paper, we propose a customized homogeneous multiprocessor for LR. The processor cores are based on transport triggered architecture (TTA). We propose some modification of the popular LR algorithm, Lenstra-Lenstra-Lovasz (LLL) for high throughput. The TTA cores are programmed with high level language. Each TTA core consists of several special function units to accelerate the program code. The multiprocessor takes 187 cycles to reduce a single matrix for LR. The architecture is synthesized on 90 nm technology and takes 405 kgates at 210 MHz.Comment: 4 pages, 3 figures, conferenc

Computationally Efficient Robust Beamforming for SINR Balancing in Multicell Downlink

We address the problem of downlink beamformer design for signal-to-interference-plus-noise ratio (SINR) balancing in a multiuser multicell environment with imperfectly estimated channels at base stations (BSs). We first present a semidefinite program (SDP) based approximate solution to the problem. Then, as our main contribution, by exploiting some properties of the robust counterpart of the optimization problem, we arrive at a second-order cone program (SOCP) based approximation of the balancing problem. The advantages of the proposed SOCP-based design are twofold. First, it greatly reduces the computational complexity compared to the SDP-based method. Second, it applies to a wide range of uncertainty models. As a case study, we investigate the performance of proposed formulations when the base station is equipped with a massive antenna array. Numerical experiments are carried out to confirm that the proposed robust designs achieve favorable results in scenarios of practical interest.Comment: 26 pages, 5 figures. Submitted for possible publicatio

Architecture Design and Implementation of the Metric First List Sphere Detector Algorithm

Soft-output detection of a multiple-input–multiple-output (MIMO) signal pose a significant challenge in future wireless systems. In this paper, we introduce a soft-output modified metric first (MMF)-LSD algorithm for MIMO detection. We design a scalable architecture and address a method to decrease memory requirements. We provide implementation results for a spatial multiplexing (SM) system with four transmitted streams and with 16- and 64-quadrature amplitude modulation (QAM) on a 0.18- m CMOS application specific integrated circuit (ASIC) technology. The MFF-LSD implementation is more efficient than the depth first (DF) -LSD in the crucial low signal-to-noise rate (SNR)region and the detection rate of the 64-QAM implementation is 39.2 Mbps@26 db with 48.2 kGEs complexity

Performance - Complexity Comparison of Receivers for a LTE MIMO–OFDM System

Implementation of receivers for spatial multiplexing multiple-input multiple-output (MIMO) orthogonal-frequency-division-multiplexing (OFDM) systems is considered. The linear minimum mean-square error (LMMSE) and the K-best list sphere detector (LSD) are compared to the iterative successive interference cancellation (SIC) detector and the iterative K-best LSD. The performance of the algorithms is evaluated in 3G long-term evolution (LTE) system. The SIC algorithm is found to perform worse than the K-best LSD when the MIMO channels are highly correlated, while the performance difference diminishes when the correlation decreases. The receivers are designed for 2X2 and 4X4 antenna systems and three different modulation schemes. Complexity results for FPGA and ASIC implementations are found. A modification to the K-best LSD which increases its detection rate is introduced. The ASIC receivers are designed to meet the decoding throughput requirements in LTE and the K-best LSD is found to be the most complex receiver although it gives the best reliable data transmission throughput. The SIC receiver has the best performance–complexity tradeoff in the 2X2 system but in the 4X4 case, the K-best LSD is the most efficient. A receiver architecture which could be reconfigured to using a simple or a more complex detector as the channel conditions change would achieve the best performance while consuming the least amount of power in the receiver

Receiver Implementation for MIMO-OFDM with AMC and Precoding

Receivers for horizontally encoded LTE based MIMO-OFDM systems are considered in this paper. Adaptive modulation and coding (AMC) is used as well as precoding. The linear minimum mean square error (LMMSE), successive interference cancellation (SIC) and K-best list sphere detectors (LSD) are compared. The receivers were designed and implemented for 2×2 and 4×4 antenna systems and meet the decoding rate requirement in LTE, i.e, 210 Mb/s in 2×2 and 405 Mb/s in 4×4 antenna systems. The results show that the performance of the receivers is similar in low SNR but the performance difference increases when a higher rank transmission is used. The K-best LSD has the highest performance and complexity. A simpler receiver could be used in the low SNRs to save power and a more complex receiver in the high SNRs when a higher goodput is needed.NokiaNokia Siemens Networks (NSN)Texas InstrumentsXilinxNational Science Foundatio