Comparison of different coding schemes for 1-bit ADC

This paper devotes to comparison of different coding schemes (various constructions of Polar and LDPC codes, Product codes and BCH codes) for the case when information is transmitted over AWGN channel with quantization with lowest possible complexity and resolution: 1-bit. We examine performance (in terms of Frame-error-rate -- FER) for schemes mentioned above and give some reasoning for results we obtained. Also we give some recommendations for choosing coding schemes for a given code rate and code length

Large-Scale-Fading Decoding in Cellular Massive MIMO Systems with Spatially Correlated Channels

Massive multiple-input--multiple-output (MIMO) systems can suffer from coherent intercell interference due to the phenomenon of pilot contamination. This paper investigates a two-layer decoding method that mitigates both coherent and non-coherent interference in multi-cell Massive MIMO. To this end, each base station (BS) first estimates the channels to intra-cell users using either minimum mean-squared error (MMSE) or element-wise MMSE (EW-MMSE) estimation based on uplink pilots. The estimates are used for local decoding on each BS followed by a second decoding layer where the BSs cooperate to mitigate inter-cell interference. An uplink achievable spectral efficiency (SE) expression is computed for arbitrary two-layer decoding schemes. A closed-form expression is then obtained for correlated Rayleigh fading, maximum-ratio combining, and the proposed large-scale fading decoding (LSFD) in the second layer. We also formulate a sum SE maximization problem with both the data power and LSFD vectors as optimization variables. Since this is an NP-hard problem, we develop a low-complexity algorithm based on the weighted MMSE approach to obtain a local optimum. The numerical results show that both data power control and LSFD improves the sum SE performance over single-layer decoding multi-cell Massive MIMO systems.Comment: 17 pages; 10 figures; Accepted for publication in IEEE Transactions on Communication

Antenna selection in massive mimo based on matching pursuit

As wireless services proliferate, the demand for available spectrum also grows. As a result, the spectral efficiency is still an issue addressed by many researchers looking for solutions to provide quality of service to a growing number of users. massive MIMO is an attractive technology for the next wireless systems since it can alleviate the expected spectral shortage. This work proposes two antenna selection strategies to be applied in the downlink of a massive MIMO system, aiming at reducing the transmission power. The proposed algorithms can also be employed to select a subset of active sensors in centralized sensor networks. The proposed strategy to select the antennas is inspired by the matching pursuit technique. The presented results show that an efficient selection can be obtained with reduced computational complexity.Com a proliferação de serviços wireless, a demanda por espectro disponível também cresce. Logo, a eficiência espectral é um assunto de grande interesse na comunidade científica, que procura por meios para fornecer qualidade de serviço ao crescente número de usuários. massive MIMO é uma técnica repleta de atrativos a ser empregada na futura geração wireless, já que aproveita o espectro existente eficientemente. Este trabalho propõe duas estratégias de seleção de antenas para serem empregadas no downlink de um sistema massive MIMO, visando a redução da potência de transmissão. Os algoritmos propostos podem também ser usados para selecionar um subconjunto de sensores ativos em uma rede centralizada de sensores. A estratégia proposta para seleção de antenas é inspirada na técnica matching pursuit. Os resultados apresentados indicam que uma seleção eficiente pode ser obtida com baixa complexidade computacional