922 research outputs found
Performance Analysis of Dual-User Macrodiversity MIMO Systems with Linear Receivers in Flat Rayleigh Fading
The performance of linear receivers in the presence of co-channel
interference in Rayleigh channels is a fundamental problem in wireless
communications. Performance evaluation for these systems is well-known for
receive arrays where the antennas are close enough to experience equal average
SNRs from a source. In contrast, almost no analytical results are available for
macrodiversity systems where both the sources and receive antennas are widely
separated. Here, receive antennas experience unequal average SNRs from a source
and a single receive antenna receives a different average SNR from each source.
Although this is an extremely difficult problem, progress is possible for the
two-user scenario. In this paper, we derive closed form results for the
probability density function (pdf) and cumulative distribution function (cdf)
of the output signal to interference plus noise ratio (SINR) and signal to
noise ratio (SNR) of minimum mean squared error (MMSE) and zero forcing (ZF)
receivers in independent Rayleigh channels with arbitrary numbers of receive
antennas. The results are verified by Monte Carlo simulations and high SNR
approximations are also derived. The results enable further system analysis
such as the evaluation of outage probability, bit error rate (BER) and
capacity.Comment: 24 pages, 7 figures; IEEE Transaction of Wireless Communication 2012
Corrected typo
Performance of Optimum Combining in a Poisson Field of Interferers and Rayleigh Fading Channels
This paper studies the performance of antenna array processing in distributed
multiple access networks without power control. The interference is represented
as a Poisson point process. Desired and interfering signals are subject to both
path-loss fading (with an exponent greater than 2) and to independent Rayleigh
fading. Using these assumptions, we derive the exact closed form expression for
the cumulative distribution function of the output
signal-to-interference-plus-noise ratio when optimum combining is applied. This
results in a pertinent measure of the network performance in terms of the
outage probability, which in turn provides insights into the network capacity
gain that could be achieved with antenna array processing. We present and
discuss examples of applications, as well as some numerical results.Comment: Submitted to IEEE Trans. on Wireless Communication (Jan. 2009
The Effect of Macrodiversity on the Performance of Maximal Ratio Combining in Flat Rayleigh Fading
The performance of maximal ratio combining (MRC) in Rayleigh channels with
co-channel interference (CCI) is well-known for receive arrays which are
co-located. Recent work in network MIMO, edge-excited cells and base station
collaboration is increasing interest in macrodiversity systems. Hence, in this
paper we consider the effect of macrodiversity on MRC performance in Rayleigh
fading channels with CCI. We consider the uncoded symbol error rate (SER) as
our performance measure of interest and investigate how different
macrodiversity power profiles affect SER performance. This is the first
analytical work in this area. We derive approximate and exact symbol error rate
results for M-QAM/BPSK modulations and use the analysis to provide a simple
power metric. Numerical results, verified by simulations, are used in
conjunction with the analysis to gain insight into the effects of the link
powers on performance.Comment: 10 pages, 5 figures; IEEE Transaction of Communication, 2012
Corrected typo
Simulations of Implementation of Advanced Communication Technologies
Wireless communication systems have seen significant advancements with the introduction of 3G, 4G, and 5G mobile standards. Since the simulation of entire systems is complex and may not allow evaluation of the impact of individual techniques, this thesis presents techniques and results for simulating the performance of advanced signaling techniques used in 3G, 4G, and 5G systems, including Code division multiple access (CDMA), Multiple Input Multiple Output (MIMO) systems, and Low-Density Parity Check (LDPC) codes. One implementation issue that is explored is the use of quantized Analog to Digital Converter (ADC) outputs and their impact on system performance.
Code division multiple access (CDMA) is a popular wireless technique, but its effectiveness is limited by factors such as multiple access interference (MAI) and the near far effect (NFE). The joint effect of sampling and quantization on the analog-digital converter (ADC) at the receiver\u27s front end has also been evaluated for different quantization bits. It has been demonstrated that 4 bits is the minimum ADC resolution sensitivity required for a reliable connection for a quantized signal with 3- and 6-dB power levels in noisy and interference-prone environments.
The demand for high data rate, reliable transmission, low bit error rate, and maximum transmission with low power has increased in wireless systems. Multiple Input Multiple Output (MIMO) systems with multiple antennas at both the transmitter and receiver side can meet these requirements by exploiting diversity and multipath propagation. The focus of MIMO systems is on improving reliability and maximizing throughput. Performance analysis of single input single output (SISO), single input multiple output (SIMO), multiple input single output (MISO), and MIMO systems is conducted using Alamouti space time block code (STBC) and Maximum Ratio Combining (MRC) technique used for transmit and receive diversity for Rayleigh fading channel under AWGN environment for BPSK and QPSK modulation schemes. Spatial Multiplexing (SM) is used to enhance spectral efficiency without additional bandwidth and power requirements. Minimum mean square error (MMSE) method is used for signal detection at the receiver end due to its low complexity and better performance. The performance of MIMO SM technique is compared for different antenna configurations and modulation schemes, and the MMSE detector is employed at the receiving end.
Advanced error correction techniques for channel coding are necessary to meet the demand for Mobile Internet in 5G wireless communications, particularly for the Internet of Things. Low Density Parity Check (LDPC) codes are used for error correction in 5G, offering high coding gain, high throughput, low latency, low power dissipation, low complexity, and rate compatibility. LDPC codes use base matrices of 5G New Radio (NR) for LDPC encoding, and a soft decision decoding algorithm is used for efficient Frame Error Rate (FER) performance. The performance of LDPC codes is assessed using a soft decision decoding layered message passing algorithm, with BPSK modulation and AWGN channel. Furthermore, the effects of quantization on LDPC codes are analyzed for both small and large numbers of quantization bits
Scaling up MIMO: Opportunities and Challenges with Very Large Arrays
This paper surveys recent advances in the area of very large MIMO systems.
With very large MIMO, we think of systems that use antenna arrays with an
order of magnitude more elements than in systems being built today, say a
hundred antennas or more. Very large MIMO entails an unprecedented number of
antennas simultaneously serving a much smaller number of terminals. The
disparity in number emerges as a desirable operating condition and a practical
one as well. The number of terminals that can be simultaneously served is
limited, not by the number of antennas, but rather by our inability to acquire
channel-state information for an unlimited number of terminals. Larger numbers
of terminals can always be accommodated by combining very large MIMO technology
with conventional time- and frequency-division multiplexing via OFDM. Very
large MIMO arrays is a new research field both in communication theory,
propagation, and electronics and represents a paradigm shift in the way of
thinking both with regards to theory, systems and implementation. The ultimate
vision of very large MIMO systems is that the antenna array would consist of
small active antenna units, plugged into an (optical) fieldbus.Comment: Accepted for publication in the IEEE Signal Processing Magazine,
October 201
DMT Optimality of LR-Aided Linear Decoders for a General Class of Channels, Lattice Designs, and System Models
The work identifies the first general, explicit, and non-random MIMO
encoder-decoder structures that guarantee optimality with respect to the
diversity-multiplexing tradeoff (DMT), without employing a computationally
expensive maximum-likelihood (ML) receiver. Specifically, the work establishes
the DMT optimality of a class of regularized lattice decoders, and more
importantly the DMT optimality of their lattice-reduction (LR)-aided linear
counterparts. The results hold for all channel statistics, for all channel
dimensions, and most interestingly, irrespective of the particular lattice-code
applied. As a special case, it is established that the LLL-based LR-aided
linear implementation of the MMSE-GDFE lattice decoder facilitates DMT optimal
decoding of any lattice code at a worst-case complexity that grows at most
linearly in the data rate. This represents a fundamental reduction in the
decoding complexity when compared to ML decoding whose complexity is generally
exponential in rate.
The results' generality lends them applicable to a plethora of pertinent
communication scenarios such as quasi-static MIMO, MIMO-OFDM, ISI,
cooperative-relaying, and MIMO-ARQ channels, in all of which the DMT optimality
of the LR-aided linear decoder is guaranteed. The adopted approach yields
insight, and motivates further study, into joint transceiver designs with an
improved SNR gap to ML decoding.Comment: 16 pages, 1 figure (3 subfigures), submitted to the IEEE Transactions
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