789 research outputs found
Symbol-Level Multiuser MISO Precoding for Multi-level Adaptive Modulation
Symbol-level precoding is a new paradigm for multiuser downlink systems which
aims at creating constructive interference among the transmitted data streams.
This can be enabled by designing the precoded signal of the multiantenna
transmitter on a symbol level, taking into account both channel state
information and data symbols. Previous literature has studied this paradigm for
MPSK modulations by addressing various performance metrics, such as power
minimization and maximization of the minimum rate. In this paper, we extend
this to generic multi-level modulations i.e. MQAM and APSK by establishing
connection to PHY layer multicasting with phase constraints. Furthermore, we
address adaptive modulation schemes which are crucial in enabling the
throughput scaling of symbol-level precoded systems. In this direction, we
design signal processing algorithms for minimizing the required power under
per-user SINR or goodput constraints. Extensive numerical results show that the
proposed algorithm provides considerable power and energy efficiency gains,
while adapting the employed modulation scheme to match the requested data rate
Energy-Efficient Symbol-Level Precoding in Multiuser MISO Based on Relaxed Detection Region
This paper addresses the problem of exploiting interference among
simultaneous multiuser transmissions in the downlink of multiple-antenna
systems. Using symbol-level precoding, a new approach towards addressing the
multiuser interference is discussed through jointly utilizing the channel state
information (CSI) and data information (DI). The interference among the data
streams is transformed under certain conditions to a useful signal that can
improve the signal-to-interference noise ratio (SINR) of the downlink
transmissions and as a result the system's energy efficiency. In this context,
new constructive interference precoding techniques that tackle the transmit
power minimization (min power) with individual SINR constraints at each user's
receiver have been proposed. In this paper, we generalize the CI precoding
design under the assumption that the received MPSK symbol can reside in a
relaxed region in order to be correctly detected. Moreover, a weighted
maximization of the minimum SNR among all users is studied taking into account
the relaxed detection region. Symbol error rate analysis (SER) for the proposed
precoding is discussed to characterize the tradeoff between transmit power
reduction and SER increase due to the relaxation. Based on this tradeoff, the
energy efficiency performance of the proposed technique is analyzed. Finally,
extensive numerical results show that the proposed schemes outperform other
state-of-the-art techniques.Comment: Submitted to IEEE transactions on Wireless Communications. arXiv
admin note: substantial text overlap with arXiv:1408.470
Constructive Multiuser Interference in Symbol Level Precoding for the MISO Downlink Channel
This paper investigates the problem of interference among the simultaneous
multiuser transmissions in the downlink of multiple antennas systems. Using
symbol level precoding, a new approach towards the multiuser interference is
discussed along this paper. The concept of exploiting the interference between
the spatial multiuser transmissions by jointly utilizing the data information
(DI) and channel state information (CSI), in order to design symbol-level
precoders, is proposed. In this direction, the interference among the data
streams is transformed under certain conditions to useful signal that can
improve the signal to interference noise ratio (SINR) of the downlink
transmissions. We propose a maximum ratio transmission (MRT) based algorithm
that jointly exploits DI and CSI to glean the benefits from constructive
multiuser interference. Subsequently, a relation between the constructive
interference downlink transmission and physical layer multicasting is
established. In this context, novel constructive interference precoding
techniques that tackle the transmit power minimization (min power) with
individual SINR constraints at each user's receivers is proposed. Furthermore,
fairness through maximizing the weighted minimum SINR (max min SINR) of the
users is addressed by finding the link between the min power and max min SINR
problems. Moreover, heuristic precoding techniques are proposed to tackle the
weighted sum rate problem. Finally, extensive numerical results show that the
proposed schemes outperform other state of the art techniques.Comment: Submitted to IEEE Transactions on Signal Processin
Degrees of Freedom of Uplink-Downlink Multiantenna Cellular Networks
An uplink-downlink two-cell cellular network is studied in which the first
base station (BS) with antennas receives independent messages from its
serving users, while the second BS with antennas transmits
independent messages to its serving users. That is, the first and second
cells operate as uplink and downlink, respectively. Each user is assumed to
have a single antenna. Under this uplink-downlink setting, the sum degrees of
freedom (DoF) is completely characterized as the minimum of
,
, , and , where denotes
. The result demonstrates that, for a broad class of network
configurations, operating one of the two cells as uplink and the other cell as
downlink can strictly improve the sum DoF compared to the conventional uplink
or downlink operation, in which both cells operate as either uplink or
downlink. The DoF gain from such uplink-downlink operation is further shown to
be achievable for heterogeneous cellular networks having hotspots and with
delayed channel state information.Comment: 22 pages, 11 figures, in revision for IEEE Transactions on
Information Theor
Transmit-Power Efficient Linear Precoding Utilizing Known Interference for the Multiantenna Downlink
It has been shown that the knowledge of both channel and data information at the base station prior to downlink transmission can help increase the received signal-to-noise ratio (SNR) of each user without the need to increase the transmitted power. Achievability is based on the idea of phase alignment (PA) precoding, where instead of nulling out the destructive interference, it judiciously rotates the phases of the transmitted symbols. In this way, they add up coherently at the intended user and yield higher received SNRs. In addition, it is well known that regularized channel inversion (RCI) precoding improves the performance of channel inversion (CI) in multiantenna downlink communications. In line with this and similar to the RCI precoding, in this paper, we propose the idea of regularized PA (RPA), which is shown to improve the performance of original PA precoding. To do this, we first rectify the original PA precoding, deriving a closed-form expression to evaluate the amount of transmit-power reduction achieved for the same average output SNR compared with CI precoding. We then use this new analysis to select the appropriate regularization factor for our proposed RPA scheme. It is shown by means of theoretical analysis and simulations that the proposed RPA precoding outperforms CI, RCI, and PA precoders from both symbol error rate (SER) and throughput perspectives and provides a more power-efficient alternative. This is particularly pronounced as the number of transmit antennas becomes larger, where up to a 50-times reduction in the transmit power is achieved by RPA (PA) compared with RCI (CI) precoding for a given performance
A Bayesian approach for adaptive multiantenna sensing in cognitive radio networks
Much of the recent work on multiantenna spectrum sensing in cognitive radio (CR) networks has been based on generalized likelihood ratio test (GLRT) detectors, which lack the ability to learn from past decisions and to adapt to the continuously changing environment. To overcome this limitation, in this paper we propose a Bayesian detector capable of learning in an efficient way the posterior distributions under both hypotheses. These posteriors summarize, in a compact way, all information seen so far by the cognitive secondary user. Our Bayesian model places priors directly on the spatial covariance matrices under both hypothesis, as well as on the probability of channel occupancy. Specifically, we use inverse-gamma and complex inverse-Wishart distributions as conjugate priors for the null and alternative hypothesis, respectively; and a binomial distribution as the prior for channel occupancy. At each sensing period, Bayesian inference is applied and the posterior for the channel occupancy is thresholded for detection. After a suitable approximation, the posteriors are employed as priors for the next sensing frame, which forms the basis of the proposed Bayesian learning procedure. We also include a forgetting mechanism that allows to operate satisfactorily on time-varying scenarios. The performance of the Bayesian detector is evaluated by simulations and also by means of CR testbed composed of universal radio peripheral (USRP) nodes. Both the simulations and our experimental measurements show that the Bayesian detector outperforms the GLRT in a variety of scenarios.The research leading to these results has received funding from the Spanish Government (MIC INN) under Projects TEC2010-19545-C04-03 (COSIMA) and CONSOLIDER-INGENIO 2010 CSD2008-00010 (COMONSENS). It also has been supported by FPI Grant BES-2011-047647
Improved reception of in-body signals by means of a wearable multi-antenna system
High data-rate wireless communication for in-body human implants is mainly performed in the 402-405 MHz Medical Implant Communication System band and the 2.45 GHz Industrial, Scientific and Medical band. The latter band offers larger bandwidth, enabling high-resolution live video transmission. Although in-body signal attenuation is larger, at least 29 dB more power may be transmitted in this band and the antenna efficiency for compact antennas at 2.45 GHz is also up to 10 times higher. Moreover, at the receive side, one can exploit the large surface provided by a garment by deploying multiple compact highly efficient wearable antennas, capturing the signals transmitted by the implant directly at the body surface, yielding stronger signals and reducing interference. In this paper, we implement a reliable 3.5 Mbps wearable textile multi-antenna system suitable for integration into a jacket worn by a patient, and evaluate its potential to improve the In-to-Out Body wireless link reliability by means of spatial receive diversity in a standardized measurement setup. We derive the optimal distribution and the minimum number of on-body antennas required to ensure signal levels that are large enough for real-time wireless endoscopy-capsule applications, at varying positions and orientations of the implant in the human body
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