• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.17-22
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• 2018

In massive multiple-input multiple-output (MIMO) systems, linear channel estimation algorithms are widely applied owing to their simple structures. However, they may cause pilot contamination, which affects the subsequent data detection performance. Therefore, herein, for an uplink multicell massive multiuser MIMO system, we consider using an alternating projection (AP) for channel estimation to eliminate the effect of pilot contamination and improve the performance of data detection in terms of the bit error rates as well. Even though the AP is nonlinear, it iteratively searches the best solution in only one dimension, and the computational complexity is thus modest. We have analyzed the mean square error with respect to the signal-to-interference ratios for both the cooperative and non-cooperative multicell scenarios. From the simulation results, we observed that the channel estimation results via the AP benefit the following signal detection more than that via the least squares for both the cooperative and non-cooperative multicell scenarios.

• Journal of Communications and Networks
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• v.15 no.4
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• pp.338-351
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• 2013

Multiple-input multiple-output (MIMO) communication may provide high spectral efficiency through the deployment of a very large number of antenna elements at the base stations. The gains from massive MIMO communication come from the use of multi-user MIMO on the uplink and downlink, but with a large excess of antennas at the base station compared to the number of served users. Initial work on massive MIMO did not fully address several practical issues associated with its deployment. This paper considers the impact of channel aging on the performance of massive MIMO systems. The effects of channel variation are characterized as a function of different system parameters assuming a simple model for the channel time variations at the transmitter. Channel prediction is proposed to overcome channel aging effects. The analytical results on aging show how capacity is lost due to time variation in the channel. Numerical results in a multicell network show that massive MIMO works even with some channel variation and that channel prediction could partially overcome channel aging effects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.185-201
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• 2023

Grant-free random access (GFRA) can reduce the access delay and signaling cost, and satisfy the short transmission packet and strict delay constraints requirement in internet of things (IoT). IoT is a major trend in the future, which is characterized by the variety of applications and devices. However, most existing studies on GFRA only consider a single type of device and omit the effect of access delay. In this paper, we study GFRA in multicell massive multipleinput multiple-output (MIMO) systems where different types of devices with various configurations and requirements co-exist. By introducing the backoff mechanism, each device is randomly activated according to the backoff parameter, and active devices randomly select an orthogonal pilot sequence from a predefined pilot pool. An analytical approximation of the average spectral efficiency for each type of device is derived. Based on it, we obtain the optimal backoff parameter for each type of devices under their delay constraints. It is found that the optimal backoff parameters are closely related to the device number and delay constraint. In general, devices that have larger quantity should have more backoff time before they are allowed to access. However, as the delay constraint become stricter, the required backoff time reduces gradually, and the device with larger quantity may have less backoff time than that with smaller quantity when its delay constraint is extremely strict. When the pilot length is short, the effect of delay constraints mentioned above works more obviously.