Fundamentals of Wireless Communication

Massive MIMO is an emerging technology for future wireless systems that has received much attention from both academia and industry recently. The most prominent feature of Massive MIMO is that the base station is equiped with a large number of antennas. It is therefore important to create scalable architectures to enable simple deployment in different configurations.In this thesis, a distributed architecture for performing the baseband processing in a massive OFDM MU-MIMO system is proposed and analyzed. The proposed architecture is based on connecting several identical nodes in a K-ary tree. It is shown that, depending on the chosen algorithms, all or most computations can be performed in a distrbuted manner. Also, the computational load of each node does not depend on the number of nodes in the tree (except for some timing issues) which implies simple scalability of the system.It is shown that it should be enough that each node contains one or two complex multipliers and a few complex adders running at a couple of hundres MHz to support specifications similar to LTE. Additionally the nodes must communicate with each other over links with data rates in the order of some Gbps.Finally, a VHDL implementation of the system is proposed. The implementation is parameterized such that a system can be generated from a given specification. Nyckelord KeywordsElektroteknik, ASIC, Massiv MIMO AbstractMassive MIMO is an emerging technology for future wireless systems that has received much attention from both academia and industry recently. The most prominent feature of Massive MIMO is that the base station is equiped with a large number of antennas. It is therefore important to create scalable architectures to enable simple deployment in different configurations.In this thesis, a distributed architecture for performing the baseband processing in a massive OFDM MU-MIMO system is proposed and analyzed. The proposed architecture is based on connecting several identical nodes in a K-ary tree. It is shown that, depending on the chosen algorithms, all or most computations can be performed in a distrbuted manner. Also, the computational load of each node does not depend on the number of nodes in the tree (except for some timing issues) which implies simple scalability of the system.It is shown that it should be enough that each node contains one or two complex multipliers and a few complex adders running at a couple of hundres MHz to support specifications similar to LTE. Additionally the nodes must communicate with each other over links with data rates in the order of some Gbps.Finally, a VHDL implementation of the system is proposed. The implementation is parameterized such that a system can be generated from a given specification.iii

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“…The cyclic prefix needs to be longer than the multipath delay in order to preserve orthogonality between subcarriers. [15]. …”

Section: Cyclic Prefixmentioning

confidence: 99%

A scalable architecture for massive MIMO base stations using distributed processing

Bertilsson

Gustafsson

Larsson

2016

2016 50th Asilomar Conference on Signals, Systems and Computers

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“…After passive suppression and analog cancellation, the strong LOS component is significantly reduced but still present and can be modeled as a Ricean distribution with K = 0 dB [5]. Hence, we generate the SI channel as (17) where ζ is uniformly distributed angle of arrival of the LOS component of the SI channel [39]. For the simulations, the signal-to-interference-noise ratio (SINR) is given by [5] …”

Section: Simulation Resultsmentioning

confidence: 99%

Superimposed signaling inspired channel estimation in full-duplex systems

Koohian

Mehrpouyan

Nasir

et al. 2018

EURASIP J. Adv. Signal Process.

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Residual self-interference (SI) cancellation in the digital baseband is an important problem in full-duplex (FD) communication systems. In this paper, we propose a new technique for estimating the SI and communication channels in a FD communication system, which is inspired from superimposed signaling. In our proposed technique, we add a constant real number to each constellation point of a conventional modulation constellation to yield asymmetric shifted modulation constellations with respect to the origin. We show mathematically that such constellations can be used for bandwidth efficient channel estimation without ambiguity. We propose an expectation maximization (EM) estimator for use with the asymmetric shifted modulation constellations. We derive a closed-form lower bound for the mean square error (MSE) of the channel estimation error, which allows us to find the minimum shift energy needed for accurate channel estimation in a given FD communication system. The simulation results show that the proposed technique outperforms the data-aided channel estimation method, under the condition that the pilots use the same extra energy as the shift, both in terms of MSE of channel estimation error and bit error rate. The proposed technique is also robust to an increasing power of the SI signal.

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“…However, according to the Appendix B.4.2 of ( [19], pp. 527-528), one way to derive the capacity of a complex-baseband channel is to think of each user of the complex channel as two uses of a real channel.…”

Section: Resultsmentioning

confidence: 99%

“…Equation (19) can be numerically calculated. However, as M becomes large, computation of the multiple infinite sum may become too prohibitive to implement.…”

Section: ) Multiple Infinite Series Representation: Thismentioning

confidence: 99%

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Outage minimization for parallel fading channels with limited feedback

Dey

2012

J Wireless Com Network

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We address an optimal power allocation problem for minimizing the outage probability for M parallel block-Nakagami-fading channels under a long-term average sum transmit power constraint with finite rate feedback of channel state information (CSI). A simulation-based optimization technique called simultaneous perturbation stochastic approximation algorithm (SPSA) is employed first to numerically derive a locally optimal power codebook. Due to the high computational complexity and long convergence time of SPSA, we make an ordering assumption on the power codebook entries and derive effective hyperplane based approximations to the channel quantization regions and present a number of low-complexity suboptimal quantized power codebook design algorithms. Unlike existing work on outage minimization for multiple-input multiple-output (MIMO) channels with limited feedback, we do not assume that identical transmission power is used for all channels within each channel quantization region. We also do not resort to a Gaussian approximation for the instantaneous mutual information in general as used in many existing work. Based on our power ordering assumption and hyperplane based approximations, we show that allocating identical power to all channels within a given channel quantization region in the limited feedback scenario is asymptotically optimal only at high average power (or average signal-to-noise ratio (SNR)) for the Rayleigh fading case, whereas for the general Nakagami case, the transmit power allocation for an individual channel within each quantized region is asymptotically proportional to the corresponding Nakagami fading parameter (severity of fading). We also present a novel diversity order result for the outage probability for the Nakagami fading case. Finally, we derive a suitable Gaussian approximation based low-complexity power allocation scheme for a large number of parallel channels, which has important applications in wideband slow-fading orthogonal frequency-division multiplexing (OFDM) systems. Extensive numerical results illustrate that only a few bits of feedback close the gap substantially in outage performance between the limited feedback case and the full instantaneous CSI at the transmitter case.

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Fundamentals of Wireless Communication

Cited by 10,612 publications

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A scalable architecture for massive MIMO base stations using distributed processing

A scalable architecture for massive MIMO base stations using distributed processing

Superimposed signaling inspired channel estimation in full-duplex systems

Outage minimization for parallel fading channels with limited feedback

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