Sherlie Portugal

Intercell Interference Coordination Using Threshold-Based Region Decisions

IMT-Advanced mobile communication systems make it possible for any devices to access high-speed networks anytime and anywhere. To meet the needs of IMT-Advanced systems, cellular systems must solve the problem of intercell interference caused by frequency reuse. Intercell interference problems become severe when orthogonal frequency division multiplexing (OFDM) transmission, which is a key technology for 4G communication systems, is used in a cellular system. In this paper, a zone-based intercell interference coordination (ICIC) scheme with high flexibility and low cost is proposed, and its performance is evaluated through multicell system-level simulations carried out according to the simplified 3GPP (3rd Generation Partnership Project) Long Term Evolution (LTE) system parameters. In the proposed algorithm, each cell is divided into several regions based on threshold values. Each region reuses frequencies in different ways, and the regions have different maximum transmit (TX) powers according to the interference environment. Even though the proposed scheme can be implemented with low complexity by using only the existing user equipment (UE) measurement, simulation results have confirmed that it provides significant improvements in geometry distribution.

Improvement of the sphere decoding complexity through an adaptive OSIC-SD system

Sphere decoding is a decoding technique able to achieve the maximum likelihood error performance in fading environments; nevertheless, it exhibits a high complexity, especially in poor channel conditions. In this paper, we present an adaptive hybrid algorithm which reduces the complexity of conventional sphere decoding without sacrificing its error performance. Through simulations, we prove that the proposed system maintains almost the same bit error rate of the conventional sphere decoding, and exhibits a lower, quasi-constant complexity.

Throughput Performance Analysis of AMC Based on a New SNR Estimation Algorithm Using Preamble

The rapid growth in mobile communication users necessitates the development of reliable communication systems that provide higher data rates. To meet these requirements, techniques such as multiple input multiple output (MIMO) and orthogonal frequency division multiplexing (OFDM) have been developed in recent years. Current research activity is focused on developing MIMO-OFDM systems that combine the benefits of both techniques. In addition, for a fast wireless channel environment, the data rate and reliability can be optimized by setting the modulation and coding adaptively according to the channel conditions, as well as by using sub-carrier frequency and power allocation techniques. The overall system performance depends on how accurately the feedback-based system obtains the channel state information and feeds it back to the transmitter without delay. In this paper, we propose a signal-to-noise ratio (SNR) estimation algorithm in which the preamble is known for both sides of the transceiver. Also, we applied AMC on several channel environments using the parameters of IEEE 802.11n and compared throughput performance using each of the different SNR Estimation Algorithm. The results obtained prove that our proposed algorithm is more accurate than traditional algorithms.

Proposal and performance analysis of a novel preamble-based SNR estimation algorithm

The latest wireless communication systems focus on developing MIMO-OFDM systems that allow the transmission of very high data rates in fading environments. We can optimize these systems even further by setting the modulation and coding adaptively according to the channel conditions, and by using sub-carrier frequency and power allocation techniques. The overall system performance depends on the accuracy and delay of the channel state information (CSI). In this paper, we propose a signal-to-noise ratio (SNR) estimation algorithm based on preamble transmission. Through simulations of several channel environments, we prove that our proposed algorithm is more accurate than conventional algorithms.

Reduction of sphere decoding complexity using an adaptive SD-OSIC system

Sphere decoding is a technique able to achieve the optimal performance of the maximum likelihood decoder, but its high and variable complexity can make the practical implementation infeasible. In this paper, we present an adaptive system, called adaptive SD-OSIC, as a way of reducing the decoding complexity while maintaining the error performance of conventional sphere decoding.

Improvement of the throughput-SNR trade-off using a 4G adaptive MCM system

The MIMO-OFDM Adaptive MCM System changes MIMO scheme, channel coding rate, and modulation scheme, adaptively, according to the channel conditions. And the addition of Pre-coding and Antenna Subset Selection assures a better performance and higher data rate. The MIMO-OFDM Adaptive MCM System achieves a better average throughput performance than a Non Adaptive-MCM system; as SNR increases, the throughput increases almost linearly. Based on the simulation results, we conclude that the proposed MIMO-OFDM Adaptive MCM System represents a feasible solution for improving the throughput-SNR tradeoff in the next generation of mobile communication systems.

Performance analysis of an adaptive-MCM system with combining AMC and MIMO schemes

In this paper, we proposed a system that combines AMC and MIMO schemes. While conventional AMC system changes only the coding rate and modulation, the proposed Adaptive-MCM system also selects the MIMO scheme (diversity, multiplexing) according to channel condition. Furthermore, by applying pre-coding and antenna subset-selection we not only produce optimal performance but also increase the data rate. In case of Non-Adaptive-MCM, the simulation results show that even thought, this system secures enough SNR, and its maximum throughput is limited. As for the Adaptive-MCM System, the simulation shows an overall average data rate increase, and a maximum throughput of 1440kbps that can be achieved because the schemes corresponding to the MCM levels are assigned dynamically. This probes that the Adaptive-MCM system increases the average data rate by improving the trade-off between SNR and throughput.