arXiv subjects

Marios Kountouris

Publications and source records attributed to Marios Kountouris.

148 records · Page 9Linked to original sources

arXiv2009

Capacity Scaling of SDMA in Wireless Ad Hoc Networks

We consider an ad hoc network in which each multi-antenna transmitter sends independent streams to multiple receivers in a Poisson field of interferers. We provide the outage probability and transmission capacity scaling laws, aiming at investigating the fundamental limits of Space Division Multiple Access (SDMA). We first show that super linear capacity scaling with the number of receive/transmit antennas can be achieved using dirty paper coding. Nevertheless, the potential benefits of multi-stream, multi-antenna communications fall off quickly if linear precoding is employed, leading to sublinear capacity growth in the case of single-antenna receivers. A key finding is that receive antenna array processing is of vital importance in SDMA ad hoc networks, as a means to cancel the increased residual interference and boost the signal power through diversity.

cs.IT↗

arXiv2008

Achievable Throughput of Multi-mode Multiuser MIMO with Imperfect CSI Constraints

For the multiple-input multiple-output (MIMO) broadcast channel with imperfect channel state information (CSI), neither the capacity nor the optimal transmission technique have been fully discovered. In this paper, we derive achievable ergodic rates for a MIMO fading broadcast channel when CSI is delayed and quantized. It is shown that we should not support too many users with spatial division multiplexing due to the residual inter-user interference caused by imperfect CSI. Based on the derived achievable rates, we propose a multi-mode transmission strategy to maximize the throughput, which adaptively adjusts the number of active users based on the channel statistics information.

cs.IT↗

arXiv2008

Mode Switching for MIMO Broadcast Channel Based on Delay and Channel Quantization

Imperfect channel state information degrades the performance of multiple-input multiple-output (MIMO) communications; its effect on single-user (SU) and multi-user (MU) MIMO transmissions are quite different. In particular, MU-MIMO suffers from residual inter-user interference due to imperfect channel state information while SU-MIMO only suffers from a power loss. This paper compares the throughput loss of both SU and MU MIMO on the downlink due to delay and channel quantization. Accurate closed-form approximations are derived for the achievable rates for both SU and MU MIMO. It is shown that SU-MIMO is relatively robust to delayed and quantized channel information, while MU MIMO with zero-forcing precoding loses spatial multiplexing gain with a fixed delay or fixed codebook size. Based on derived achievable rates, a mode switching algorithm is proposed that switches between SU and MU MIMO modes to improve the spectral efficiency, based on the average signal-to-noise ratio (SNR), the normalized Doppler frequency, and the channel quantization codebook size. The operating regions for SU and MU modes with different delays and codebook sizes are determined, which can be used to select the preferred mode. It is shown that the MU mode is active only when the normalized Doppler frequency is very small and the codebook size is large.

cs.IT↗

arXiv2007

Joint power control and user scheduling in multicell wireless networks: Capacity scaling laws

We address the optimization of the sum rate performance in multicell interference-limited singlehop networks where access points are allowed to cooperate in terms of joint resource allocation. The resource allocation policies considered here combine power control and user scheduling. Although very promising from a conceptual point of view, the optimization of the sum of per-link rates hinges, in principle, on tough issues such as computational complexity and the requirement for heavy receiver-to-transmitter channel information feedback across all network cells. In this paper, we show that, in fact, distributed algorithms are actually obtainable in the asymptotic regime where the numbers of users per cell is allowed to grow large. Additionally, using extreme value theory, we provide scaling laws for upper and lower bounds for the network capacity (sum of single user rates over all cells), corresponding to zero-interference and worst-case interference scenarios. We show that the scaling is either dominated by path loss statistics or by small-scale fading, depending on the regime and user location scenario. We show that upper and lower rate bounds behave in fact identically, asymptotically. This remarkable result suggests not only that distributed resource allocation is practically possible but also that the impact of multicell interference on the capacity (in terms of scaling) actually vanishes asymptotically.

cs.IT↗