5 research outputs found
Massive MIMO with Non-Ideal Arbitrary Arrays: Hardware Scaling Laws and Circuit-Aware Design
Massive multiple-input multiple-output (MIMO) systems are cellular networks
where the base stations (BSs) are equipped with unconventionally many antennas,
deployed on co-located or distributed arrays. Huge spatial degrees-of-freedom
are achieved by coherent processing over these massive arrays, which provide
strong signal gains, resilience to imperfect channel knowledge, and low
interference. This comes at the price of more infrastructure; the hardware cost
and circuit power consumption scale linearly/affinely with the number of BS
antennas . Hence, the key to cost-efficient deployment of large arrays is
low-cost antenna branches with low circuit power, in contrast to today's
conventional expensive and power-hungry BS antenna branches. Such low-cost
transceivers are prone to hardware imperfections, but it has been conjectured
that the huge degrees-of-freedom would bring robustness to such imperfections.
We prove this claim for a generalized uplink system with multiplicative
phase-drifts, additive distortion noise, and noise amplification. Specifically,
we derive closed-form expressions for the user rates and a scaling law that
shows how fast the hardware imperfections can increase with while
maintaining high rates. The connection between this scaling law and the power
consumption of different transceiver circuits is rigorously exemplified. This
reveals that one can make the circuit power increase as , instead of
linearly, by careful circuit-aware system design.Comment: Accepted for publication in IEEE Transactions on Wireless
Communications, 16 pages, 8 figures. The results can be reproduced using the
following Matlab code: https://github.com/emilbjornson/hardware-scaling-law
Massive MIMO for Maximal Spectral Efficiency: How Many Users and Pilots Should Be Allocated?
Massive MIMO is a promising technique to increase the spectral efficiency
(SE) of cellular networks, by deploying antenna arrays with hundreds or
thousands of active elements at the base stations and performing coherent
transceiver processing. A common rule-of-thumb is that these systems should
have an order of magnitude more antennas, , than scheduled users, ,
because the users' channels are likely to be near-orthogonal when .
However, it has not been proved that this rule-of-thumb actually maximizes the
SE. In this paper, we analyze how the optimal number of scheduled users,
, depends on and other system parameters. To this end, new SE
expressions are derived to enable efficient system-level analysis with power
control, arbitrary pilot reuse, and random user locations. The value of
in the large- regime is derived in closed form, while simulations
are used to show what happens at finite , in different interference
scenarios, with different pilot reuse factors, and for different processing
schemes. Up to half the coherence block should be dedicated to pilots and the
optimal is less than 10 in many cases of practical relevance.
Interestingly, depends strongly on the processing scheme and hence it
is unfair to compare different schemes using the same .Comment: To appear in IEEE Transactions on Wireless Communications, 16 pages,
14 figure
Simulación computacional y paralelización de un sistema de comunicaciones inalámbrico MIMO: Estimación del Canal y Decodificación de Señales
En la presente tesis se realiza un estudio de todo el proceso de una comunicación
en un sistema MIMO, desde la estimación de las condiciones del canal, hasta la decodificación de la señal, utilizando algoritmos de ramificación y poda (ASD), y paralelizando los algoritmos sobre Unidades Gráficas de Proceso (GPU).Puig Borrás, V. (2011). Simulación computacional y paralelización de un sistema de comunicaciones inalámbrico MIMO: Estimación del Canal y Decodificación de Señales. http://hdl.handle.net/10251/1136