70 research outputs found
Energy Efficient ADC Bit Allocation and Hybrid Combining for Millimeter Wave MIMO Systems
Low resolution analog-to-digital converters (ADCs) can be employed to improve
the energy efficiency (EE) of a wireless receiver since the power consumption
of each ADC is exponentially related to its sampling resolution and the
hardware complexity. In this paper, we aim to jointly optimize the sampling
resolution, i.e., the number of ADC bits, and analog/digital hybrid combiner
matrices which provides highly energy efficient solutions for millimeter wave
multiple-input multiple output systems. A novel decomposition of the hybrid
combiner to three parts is introduced: the analog combiner matrix, the bit
resolution matrix and the baseband combiner matrix. The unknown matrices are
computed as the solution to a matrix factorization problem where the optimal,
fully digital combiner is approximated by the product of these matrices. An
efficient solution based on the alternating direction method of multipliers is
proposed to solve this problem. The simulation results show that the proposed
solution achieves high EE performance when compared with existing benchmark
techniques that use fixed ADC resolutions
Resource Allocation for Licensed/Unlicensed Carrier Aggregation MIMO Systems
In this paper a novel Carrier Aggregation (CA)
scheme is proposed for downlink MIMO LTE-A Systems. The
proposed approach achieves increased transmission rates by
establishing the communication links via both licensed and
unlicensed bands without generating or experiencing interference
to/from the users of the latter bands. To that end, a rate
optimization problem is defined and solved subject to the previous
zero interference constraints, a total power constraint and a
maximum number of aggregated bands constraint. It turns
out that the previous problem is a Mixed Integer Non Linear
Programming (MINLP) one that requires an exhaustive search
procedure in order to be solved. To tackle this, an optimal low
complexity method is proposed based on the Lagrange dual
decomposition. The performance of the original (MINLP) and
the low-complexity proposed techniques is verified via indicative
simulation
Resource allocation for licensed/unlicensed carrier aggregation MIMO systems
In this paper a novel Carrier Aggregation (CA) scheme is proposed for downlink MIMO LTE-A Systems. The proposed approach achieves increased transmission rates by establishing the communication links via both licensed and unlicensed bands without generating or experiencing interference to/from the users of the latter bands. To that end, a rate optimization problem is defined and solved subject to the previous zero interference constraints, a total power constraint and a maximum number of aggregated bands constraint
Joint Bit Allocation and Hybrid Beamforming Optimization for Energy Efficient Millimeter Wave MIMO Systems
In this paper, we aim to design highly energy efficient end-to-end
communication for millimeter wave multiple-input multiple-output systems. This
is done by jointly optimizing the digital-to-analog converter
(DAC)/analog-to-digital converter (ADC) bit resolutions and hybrid beamforming
matrices. The novel decomposition of the hybrid precoder and the hybrid
combiner to three parts is introduced at the transmitter (TX) and the receiver
(RX), respectively, representing the analog precoder/combiner matrix, the
DAC/ADC bit resolution matrix and the baseband precoder/combiner matrix. The
unknown matrices are computed as a solution to the matrix factorization problem
where the optimal fully digital precoder or combiner is approximated by the
product of these matrices. A novel and efficient solution based on the
alternating direction method of multipliers is proposed to solve these problems
at both the TX and the RX. The simulation results show that the proposed
solution, where the DAC/ADC bit allocation is dynamic during operation,
achieves higher energy efficiency when compared with existing benchmark
techniques that use fixed DAC/ADC bit resolutions.Comment: arXiv admin note: text overlap with arXiv:1909.1217
Weak Interference Detection with Signal Cancellation in Satellite Communications
Interference is identified as a critical issue for satellite communication (SATCOM) systems and services. There is a growing concern in the satellite industry to manage and mitigate interference efficiently. While there are efficient techniques to monitor strong interference in SATCOM, weak interference is not so easily detected because of its low interference to signal and noise ratio (ISNR). To address this issue, this paper proposes and develops a technique which takes place on-board the satellite by decoding the desired signal, removing it from the total received signal and applying an Energy Detector (ED) in the remaining signal for the detection of interference. Different from the existing literature, this paper considers imperfect signal cancellation, examining how the decoding errors affect the sensing performance, derives the expressions for the probability of false alarm and provides a set of simulations results, verifying the efficiency of the technique
Multi-Antenna Data-Driven Eavesdropping Attacks and Symbol-Level Precoding Countermeasures
In this work, we consider secure communications in wireless multi-user (MU)
multiple-input single-output (MISO) systems with channel coding in the presence
of a multi-antenna eavesdropper (Eve). In this setting, we exploit machine
learning (ML) tools to design soft and hard decoding schemes by using precoded
pilot symbols as training data. In this context, we propose ML frameworks for
decoders that allow an Eve to determine the transmitted message with high
accuracy. We thereby show that MU-MISO systems are vulnerable to such
eavesdropping attacks even when relatively secure transmission techniques are
employed, such as symbol-level precoding (SLP). To counteract this attack, we
propose two novel SLP-based schemes that increase the bit-error rate at Eve by
impeding the learning process. We design these two security-enhanced schemes to
meet different requirements regarding complexity, security, and power
consumption. Simulation results validate both the ML-based eavesdropping
attacks as well as the countermeasures, and show that the gain in security is
achieved without affecting the decoding performance at the intended users.Comment: Submitted to the IEEE Transactions on Information Forensics and
Securit
On-board the Satellite Interference Detection with Imperfect Signal Cancellation
Interference issues have been identified as a threat for satellite communication systems and services, resulting in throughput degradation and revenue loss to the satellite operators. In this context, an on-board spectrum monitoring unit (SMU) can be used to detect interference reliably. Current satellite SMUs are deployed on the ground and the introduction of an in-orbit SMU can bring several benefits, e.g. simplifying the ground based station in multibeam systems. This paper proposes a two-step algorithm for on-board interference detection, exploiting the frame structure of DVB-S2X standard, which employs pilot symbols for data transmission. Assuming that the pilot signal is known at the receiver, it can be removed from the total received signal. Then, an Energy Detection (ED) technique can be applied on the remaining signal in order to decide the presence or absence of interference. The simulation results show that the proposed technique outperforms the conventional ED in low interference-to-signal and noise ratios (ISNRs)
Green joint radar-communications: RF selection with low resolution DACs and hybrid precoding
This paper considers a multiple-input multiple-output (MIMO) joint radar-communication (JRC) transmission with hybrid precoding and low resolution digital to analog converters (DACs). An energy efficient radio frequency (RF) chain and DAC bit selection approach is presented for a subarrayed hybrid MIMO JRC system. We introduce a weighting formulation to represent the combined radar-communications information rate. The presented selection mechanism is incorporated with fractional programming to solve an energy efficiency maximization problem for JRC which selects the optimal number of RF chains and DAC bit resolution. Subsequently, a weighted minimization problem to compute the precoding matrices is formulated, which is solved using an alternating minimization approach. The numerical results show the effectiveness of the proposed method in terms of high energy efficiency whilst maintaining good rate and desirable radar beampattern performance
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