Design of 4 &amp;#x00D7; 4 MIMO-OFDMA receiver with precode codebook search for 3GPP-LTE

Lee, Chia-Ching; Liao, Chun-Fu; Chen, Chao-Ming; Huang, Yuan-Hao

doi:10.1109/iscas.2010.5537676

Cited by 6 publications

(4 citation statements)

References 6 publications

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“…For the set of given tasks, the task execution times, utilization, and different costs associated with PU types are obtained from [1] and [16]- [22]. The utilization of the different tasks on OpenRISC, TABLE I DESCRIPTION OF REALISTIC BENCHMARKS TABLE II DESCRIPTION OF THE USED PU TYPES ARM-Cortex-A9, and Ultra-SPARC-T1 is calculated as the ratio between task execution time and task deadline based on the application throughput.…”

Section: Performance Resultsmentioning

confidence: 99%

Energy Aware Mapping for Reconfigurable Wireless MPSoCs

Hussien

Amin

Eltawil

et al. 2015

IEEE Trans. VLSI Syst.

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Abstract-Energy management for multimode software defined radio systems remains a daunting challenge. This brief develops a high level framework that generates a multiprocessor systems on chip architecture from a library of heterogeneous processing resources that can be reconfigured to support various modes of operation. The framework proposes joint task and core mapping with system level floorplanning. With the objective of minimizing energy, we develop an analytical probabilistic model that considers static, dynamic, configuration, and communication energy components for multiple applications characterized by probabilities of execution. Finally, a fast energy aware joint task and core mapping heuristic is proposed and performance is demonstrated on realistic benchmarks. Index Terms-Core mapping, multiprocessor systems on chip (MPSoC), synthesis, task mapping. I. INTRODUCTIONThe rich space of applications/configurations required of modern wireless systems creates a wide range of scenarios that mandates an energy efficient reconfigurable platform. Recently, multiprocessor systems on chip (MPSoC) architectures have evolved rapidly in the race to flexible high-performance embedded computing. This is particularly true for multimode communication systems that require high flexibility and low power simultaneously. Toward that end, numerous techniques have been developed to optimize energy consumption. A key realization that energy aware techniques utilize is that efficiency is highly related to the nature of the application. Usually, the set of target applications can be characterized stochastically where each type of application is represented by a certain execution probability. These probabilities can be obtained through statistical information collected from each user regularly. The consideration of these execution probabilities affects system performance and energy efficiency. For example, a mode with high execution probability should be mapped to lower power processors satisfying the execution requirements to obtain an energy efficient system. Energy optimization techniques presented in prior work consider only processing energy, or communication energy or both. However, the consideration of reconfiguration energy was neglected. It is important to consider the reconfiguration energy required to switch the processing units (PUs) between different tasks, which would be the expected mode of operation for a multireconfigurable platform that supports different radio access technologies. The reconfiguration cost is highly dependent on the architecture and structure of the platform. For example, if a reconfigurable fabric is used then there is a reconfiguration energy cost associated with the change of configuration bits of configurable logic blocks (CLBs), and connections

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Section: Performance Resultsmentioning

confidence: 99%

Energy Aware Mapping for Reconfigurable Wireless MPSoCs

Hussien

Amin

Eltawil

et al. 2015

IEEE Trans. VLSI Syst.

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“…Only very little overhead is required for the hardware to switch between the two modes. A receiver with small chip area for the practical multi-mode MIMO system is possible [7]. Thus, our tree search based codeword selection is very attractive in this scenario.…”

Section: Discussionmentioning

confidence: 99%

“…where the QRD of H = D h 2 h 4 h 3 h 1 = Q R is used. The breadth-first tree traversal is then applied to find the target c opt in (7).…”

Section: Proposed Codeword Selection Algorithmmentioning

confidence: 99%

“…An important issue at the receiver side of a beamforming system is to determine the target codeword from a codebook with low complexity. This fast codeword selection scheme is important for the low-cost implementation of a baseband receiver [7]. The order and bound algorithm [3] finds the target codeword by searching sequentially over the codewords in the order of decreasing chordal distance to the optimal beamforming vector.…”

Section: Introductionmentioning

confidence: 99%

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Fast codeword selection for limited feedback beamforming multiple‐input–multiple‐output systems using breadth‐first tree search

2013

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Codebooks with constant modulus entries are being considered for the limited feedback beamforming multiple-inputmultiple-output (MIMO) system to improve the power amplifier efficiency at the transmitter. Assume that one such codebook is known to both the transmitter and receiver. The receiver must determine a target codeword from this codebook and send its index back to the transmitter. A receiver can be implemented with low cost if fast codeword selection algorithm is executed. In this study, the authors utilise the properties possessed by three such codebooks and propose a novel tree search algorithm for fast codeword selection. Compared with two previously reported codeword selection algorithms, our algorithm is of fixed complexity and does find the target codeword. Furthermore, our algorithm for codeword selection is similar to the tree search for MIMO detection. These two similar tree search algorithms for both codeword selection and MIMO detection can be implemented by the same hardware architecture. A baseband receiver with small chip area for the dual-mode (the spatial multiplexing and beamforming transmission modes) MIMO system is possible.

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Precoder selection under K-best MIMO detection for 3GPP-LTE/LTE-A systems

Wang

Tsai

2012

2012 18th Asia-Pacific Conference on Communications (APCC)

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Design of 4 × 4 MIMO-OFDMA receiver with precode codebook search for 3GPP-LTE

Cited by 6 publications

References 6 publications

Energy Aware Mapping for Reconfigurable Wireless MPSoCs

Energy Aware Mapping for Reconfigurable Wireless MPSoCs

Fast codeword selection for limited feedback beamforming multiple‐input–multiple‐output systems using breadth‐first tree search

Precoder selection under K-best MIMO detection for 3GPP-LTE/LTE-A systems

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