Comparative Analysis of Channel Estimation Techniques in SISO, MISO and MIMO Systems

The ever-growing need for high data rate, bandwidthefficiency, reliability, less complexity and less power consumptionin our communication systems is on the increase.Modern techniques have to be developed and put in place tomeet these requirements. Research has shown, that compared toconventional Single input Single output (SISO) systems, MultipleinputSingle output (MISO), and Multiple-input multiple-output(MIMO) can actually increase the data rate of a communicationsystem, without actually requiring more transmit power orbandwidth. This paper aims at the investigation of the existingchannel estimation techniques. Based on the pilot arrangement,the block type and comb type are compared, employing theLeast Square estimation (L.S) and Minimum Mean SquaredError (MMSE) estimators. Pilots occupy bandwidth, minimizingthe number of pilots used to estimate the channel, in orderto allow for more bandwidth utilization for data transmission,without compromising the accuracy of the estimates is takeninto consideration. Various channel interpolation techniques andpilot-data insertion ratio are investigated, simulated and compared,to determine the best performance technique with lesscomplexity and minimum power consumption. As performancemeasures, the Mean squared error (MSE) and Bit error rate(BER) as a function of Signal to noise power ratio (SNR) ofthe different channel estimation techniques are plotted, in orderto identify the technique with the most optimal performance.The complexity and energy efficiency of the techniques are alsoinvestigated. The system modelling and simulations are carriedout using Matlab simulation package. The MIMO gives theoptimum performance, followed by the MISO and SISO. Thisis as a result of the diversity and multiplexing gain experiencedin the multiple antenna techniques using the STBC

Comparative Analysis of Channel Estimation Techniques in SISO, MISO and MIMO Systems

Abstract—The ever-growing need for high data rate, bandwidth efficiency, reliability, less complexity and less power consumption in our communication systems is on the increase. Modern techniques have to be developed and put in place to meet these requirements. Research has shown, that compared to conventional Single Input Single Output (SISO) systems, Multiple- Input Single Output (MISO), and Multiple-Input Multiple- Output (MIMO) can actually increase the data rate of a communication system, without actually requiring more transmit power or bandwidth. This paper aims at the investigation of the existing channel estimation techniques. Based on the pilot arrangement, the block type and comb type are compared, employing the Least Square estimation (L.S) and Minimum Mean Squared Error (MMSE) estimators. Pilots occupy bandwidth, minimizing the number of pilots used to estimate the channel, in order to allow for more bandwidth utilization for data transmission, without compromising the accuracy of the estimates is taken into consideration. Various channel interpolation techniques and pilot-data insertion ratio are investigated, simulated and compared, to determine the best performance technique with less complexity and minimum power consumption. As performance measures, the Mean Squared Error (MSE) and Bit Error Rate (BER) as a function of Signal to Noise power Ratio (SNR) of the different channel estimation techniques are plotted, in order to identify the technique with the most optimal performance. The complexity and energy efficiency of the techniques are also investigated. The system modelling and simulations are carried out using Matlab simulation package. The MIMO gives the optimum performance, followed by the MISO and SISO. This is as a result of the diversity and multiplexing gain experienced in the multiple antenna techniques using the STBC

Comparative Analysis of Channel Estimation Techniques in SISO, MISO and MIMO Systems

The ever-growing need for high data rate, bandwidth efficiency, reliability, less complexity and less power consumption in our communication systems is on the increase. Modern techniques have to be developed and put in place to meet these requirements. Research has shown, that compared to conventional Single input Single output (SISO) systems, Multipleinput Single output (MISO), and Multiple-input multiple-output (MIMO) can actually increase the data rate of a communication system, without actually requiring more transmit power or bandwidth. This paper aims at the investigation of the existing channel estimation techniques. Based on the pilot arrangement, the block type and comb type are compared, employing the Least Square estimation (L.S) and Minimum Mean Squared Error (MMSE) estimators. Pilots occupy bandwidth, minimizing the number of pilots used to estimate the channel, in order to allow for more bandwidth utilization for data transmission, without compromising the accuracy of the estimates is taken into consideration. Various channel interpolation techniques and pilot-data insertion ratio are investigated, simulated and compared, to determine the best performance technique with less complexity and minimum power consumption. As performance measures, the Mean squared error (MSE) and Bit error rate (BER) as a function of Signal to noise power ratio (SNR) of the different channel estimation techniques are plotted, in order to identify the technique with the most optimal performance. The complexity and energy efficiency of the techniques are also investigated. The system modelling and simulations are carried out using Matlab simulation package. The MIMO gives the optimum performance, followed by the MISO and SISO. This is as a result of the diversity and multiplexing gain experienced in the multiple antenna techniques using the STBC

Robust massive MIMO Equilization for mmWave systems with low resolution ADCs

Leveraging the available millimeter wave spectrum will be important for 5G. In this work, we investigate the performance of digital beamforming with low resolution ADCs based on link level simulations including channel estimation, MIMO equalization and channel decoding. We consider the recently agreed 3GPP NR type 1 OFDM reference signals. The comparison shows sequential DCD outperforms MMSE-based MIMO equalization both in terms of detection performance and complexity. We also show that the DCD based algorithm is more robust to channel estimation errors. In contrast to the common believe we also show that the complexity of MMSE equalization for a massive MIMO system is not dominated by the matrix inversion but by the computation of the Gram matrix.Comment: submitted to WCNC 2018 Workshop

Towards a Realistic Assessment of Multiple Antenna HCNs: Residual Additive Transceiver Hardware Impairments and Channel Aging

Given the critical dependence of broadcast channels by the accuracy of channel state information at the transmitter (CSIT), we develop a general downlink model with zero-forcing (ZF) precoding, applied in realistic heterogeneous cellular systems with multiple antenna base stations (BSs). Specifically, we take into consideration imperfect CSIT due to pilot contamination, channel aging due to users relative movement, and unavoidable residual additive transceiver hardware impairments (RATHIs). Assuming that the BSs are Poisson distributed, the main contributions focus on the derivations of the upper bound of the coverage probability and the achievable user rate for this general model. We show that both the coverage probability and the user rate are dependent on the imperfect CSIT and RATHIs. More concretely, we quantify the resultant performance loss of the network due to these effects. We depict that the uplink RATHIs have equal impact, but the downlink transmit BS distortion has a greater impact than the receive hardware impairment of the user. Thus, the transmit BS hardware should be of better quality than user's receive hardware. Furthermore, we characterise both the coverage probability and user rate in terms of the time variation of the channel. It is shown that both of them decrease with increasing user mobility, but after a specific value of the normalised Doppler shift, they increase again. Actually, the time variation, following the Jakes autocorrelation function, mirrors this effect on coverage probability and user rate. Finally, we consider space division multiple access (SDMA), single user beamforming (SU-BF), and baseline single-input single-output (SISO) transmission. A comparison among these schemes reveals that the coverage by means of SU-BF outperforms SDMA in terms of coverage.Comment: accepted in IEEE TV