3,667 research outputs found
Simultaneous Transmission and Reception: Algorithm, Design and System Level Performance
Full Duplex or Simultaneous transmission and reception (STR) in the same
frequency at the same time can potentially double the physical layer capacity.
However, high power transmit signal will appear at receive chain as echoes with
powers much higher than the desired received signal. Therefore, in order to
achieve the potential gain, it is imperative to cancel these echoes. As these
high power echoes can saturate low noise amplifier (LNA) and also digital
domain echo cancellation requires unrealistically high resolution
analog-to-digital converter (ADC), the echoes should be cancelled or suppressed
sufficiently before LNA. In this paper we present a closed-loop echo
cancellation technique which can be implemented purely in analogue domain. The
advantages of our method are multiple-fold: it is robust to phase noise, does
not require additional set of antennas, can be applied to wideband signals and
the performance is irrelevant to radio frequency (RF) impairments in transmit
chain. Next, we study a few protocols for STR systems in carrier sense multiple
access (CSMA) network and investigate MAC level throughput with realistic
assumptions in both single cell and multiple cells. We show that STR can reduce
hidden node problem in CSMA network and produce gains of up to 279% in maximum
throughput in such networks. Finally, we investigate the application of STR in
cellular systems and study two new unique interferences introduced to the
system due to STR, namely BS-BS interference and UE-UE interference. We show
that these two new interferences will hugely degrade system performance if not
treated appropriately. We propose novel methods to reduce both interferences
and investigate the performances in system level.Comment: 20 pages. This manuscript will appear in the IEEE Transactions on
Wireless Communication
Massive MIMO for Internet of Things (IoT) Connectivity
Massive MIMO is considered to be one of the key technologies in the emerging
5G systems, but also a concept applicable to other wireless systems. Exploiting
the large number of degrees of freedom (DoFs) of massive MIMO essential for
achieving high spectral efficiency, high data rates and extreme spatial
multiplexing of densely distributed users. On the one hand, the benefits of
applying massive MIMO for broadband communication are well known and there has
been a large body of research on designing communication schemes to support
high rates. On the other hand, using massive MIMO for Internet-of-Things (IoT)
is still a developing topic, as IoT connectivity has requirements and
constraints that are significantly different from the broadband connections. In
this paper we investigate the applicability of massive MIMO to IoT
connectivity. Specifically, we treat the two generic types of IoT connections
envisioned in 5G: massive machine-type communication (mMTC) and ultra-reliable
low-latency communication (URLLC). This paper fills this important gap by
identifying the opportunities and challenges in exploiting massive MIMO for IoT
connectivity. We provide insights into the trade-offs that emerge when massive
MIMO is applied to mMTC or URLLC and present a number of suitable communication
schemes. The discussion continues to the questions of network slicing of the
wireless resources and the use of massive MIMO to simultaneously support IoT
connections with very heterogeneous requirements. The main conclusion is that
massive MIMO can bring benefits to the scenarios with IoT connectivity, but it
requires tight integration of the physical-layer techniques with the protocol
design.Comment: Submitted for publicatio
Feedback Mechanisms for Centralized and Distributed Mobile Systems
The wireless communication market is expected to witness considerable growth in the immediate future due to increasing smart device usage to access real-time data. Mobile devices become the predominant method of Internet access via cellular networks (4G/5G) and the onset of virtual reality (VR), ushering in the wide deployment of multiple bands, ranging from TVWhite Spaces to cellular/WiFi bands and on to mmWave. Multi-antenna techniques have been considered to be promising approaches in telecommunication to optimize the utilization of radio spectrum and minimize the cost of system construction. The performance of multiple antenna technology depends on the utilization of radio propagation properties and feedback of such information in a timely manner. However, when a signal is transmitted, it is usually dispersed over time coming over different paths of different lengths due to reflections from obstacles or affected by Doppler shift in mobile environments. This motivates the design of novel feedback mechanisms that improve the performance of multi-antenna systems. Accurate channel state information (CSI) is essential to increasing throughput in multiinput, multi-output (MIMO) systems with digital beamforming. Channel-state information for the operation of MIMO schemes (such as transmit diversity or spatial multiplexing) can be acquired by feedback of CSI reports in the downlink direction, or inferred from uplink measurements assuming perfect channel reciprocity (CR). However, most works make the assumption that channels are perfectly reciprocal. This assumption is often incorrect in practice due to poor channel estimation and imperfect channel feedback. Instead, experiments have demonstrated that channel reciprocity can be easily broken by multiple factors. Specifically, channel reciprocity error (CRE) introduced by transmitter-receiver imbalance have been widely studied by both simulations and experiments, and the impact of mobility and estimation error have been fully investigated in this thesis. In particular, unmanned aerial vehicles (UAVs) have asymmetric behavior when communicating with one another and to the ground, due to differences in altitude that frequently occur. Feedback mechanisms are also affected by channel differences caused by the user’s body. While there has been work to specifically quantify the losses in signal reception, there has been little work on how these channel differences affect feedback mechanisms.
In this dissertation, we perform system-level simulations, implement design with a software defined radio platform, conduct in-field experiments for various wireless communication systems to analyze different channel feedback mechanisms. To explore the feedback mechanism, we then explore two specific real world scenarios, including UAV-based beamforming communications, and user-induced feedback systems
AirSync: Enabling Distributed Multiuser MIMO with Full Spatial Multiplexing
The enormous success of advanced wireless devices is pushing the demand for
higher wireless data rates. Denser spectrum reuse through the deployment of
more access points per square mile has the potential to successfully meet the
increasing demand for more bandwidth. In theory, the best approach to density
increase is via distributed multiuser MIMO, where several access points are
connected to a central server and operate as a large distributed multi-antenna
access point, ensuring that all transmitted signal power serves the purpose of
data transmission, rather than creating "interference." In practice, while
enterprise networks offer a natural setup in which distributed MIMO might be
possible, there are serious implementation difficulties, the primary one being
the need to eliminate phase and timing offsets between the jointly coordinated
access points.
In this paper we propose AirSync, a novel scheme which provides not only time
but also phase synchronization, thus enabling distributed MIMO with full
spatial multiplexing gains. AirSync locks the phase of all access points using
a common reference broadcasted over the air in conjunction with a Kalman filter
which closely tracks the phase drift. We have implemented AirSync as a digital
circuit in the FPGA of the WARP radio platform. Our experimental testbed,
comprised of two access points and two clients, shows that AirSync is able to
achieve phase synchronization within a few degrees, and allows the system to
nearly achieve the theoretical optimal multiplexing gain. We also discuss MAC
and higher layer aspects of a practical deployment. To the best of our
knowledge, AirSync offers the first ever realization of the full multiuser MIMO
gain, namely the ability to increase the number of wireless clients linearly
with the number of jointly coordinated access points, without reducing the per
client rate.Comment: Submitted to Transactions on Networkin
Scheduling for next generation WLANs: filling the gap between offered and observed data rates
In wireless networks, opportunistic scheduling is used to increase system throughput by exploiting multi-user diversity. Although recent advances have increased physical layer data rates supported in wireless local area networks (WLANs), actual throughput realized are significantly lower due to overhead. Accordingly, the frame aggregation concept is used in next generation WLANs to improve efficiency. However, with frame aggregation, traditional opportunistic schemes are no longer optimal. In this paper, we propose schedulers that take queue and channel conditions into account jointly, to maximize throughput observed at the users for next generation WLANs. We also extend this work to design two schedulers that perform block scheduling for maximizing network throughput over multiple transmission sequences. For these schedulers, which make decisions over long time durations, we model the system using queueing theory and determine users' temporal access proportions according to this model. Through detailed simulations, we show that all our proposed algorithms offer significant throughput improvement, better fairness, and much lower delay compared with traditional opportunistic schedulers, facilitating the practical use of the evolving standard for next generation wireless networks
Channel Estimation in Multicarrier Communication Systems
The data rate and spectrum efficiency of wireless mobile communications have been significantly improved over the last decade or so. Recently, the advanced systems such as 3GPP LTE and terrestrial digital TV broadcasting have been
sophisticatedly developed using OFDM and CDMA technology. In general, most mobile communication systems transmit bits of information in the radio space to the receiver. The radio channels in mobile radio systems are usually multipath fading channels, which cause inter-symbol interference (ISI) in the received signal. To remove ISI from the signal, there is a need of strong equalizer which requires knowledge on the channel impulse response (CIR).This is primarily provided by a separate channel estimator. Usually the channel estimation is based on the known sequence of bits, which is unique for a certain transmitter and which is repeated in every transmission burst. Thus, the channel estimator is able to estimate CIR for each burst separately by exploiting the known transmitted bits and the corresponding received samples.
In this thesis we investigate and compare various efficient channel estimation schemes for OFDM systems which can also be extended to MC DS-CDMA systems.The channel estimation can be performed by either inserting pilot tones into all subcarriers of OFDM symbols with a specific period or inserting pilot tones into each OFDM symbol. Two major types of pilot arrangement such as block type and comb type
pilot have been focused employing Least Square Error (LSE) and Minimum Mean Square Error (MMSE) channel estimators. Block type pilot sub-carriers is especially suitable for slow-fading radio channels whereas comb type pilots provide
better resistance to fast fading channels. Also comb type pilot arrangement is sensitive to frequency selectivity when comparing to block type arrangement. However, there is
another supervised technique called Implicit Training (IT) based channel estimation which exploits the first order statistics in the received data, induced by superimposing
periodic training sequences with good correlation properties, along with the information symbols. Hence, the need for additional time slots for training the equalizer is avoided. The performance of the estimators is presented in terms of the mean square estimation error (MSEE) and bit error rate (BER)
Energy efficient data collection and dissemination protocols in self-organised wireless sensor networks
Wireless sensor networks (WSNs) are used for event detection and data collection in
a plethora of environmental monitoring applications. However a critical factor limits
the extension of WSNs into new application areas: energy constraints. This thesis
develops self-organising energy efficient data collection and dissemination protocols in
order to support WSNs in event detection and data collection and thus extend the use
of sensor-based networks to many new application areas.
Firstly, a Dual Prediction and Probabilistic Scheduler (DPPS) is developed. DPPS
uses a Dual Prediction Scheme combining compression and load balancing techniques
in order to manage sensor usage more efficiently. DPPS was tested and evaluated
through computer simulations and empirical experiments. Results showed that DPPS
reduces energy consumption in WSNs by up to 35% while simultaneously maintaining
data quality and satisfying a user specified accuracy constraint.
Secondly, an Adaptive Detection-driven Ad hoc Medium Access Control (ADAMAC)
protocol is developed. ADAMAC limits the Data Forwarding Interruption problem
which causes increased end-to-end delay and energy consumption in multi-hop sensor
networks. ADAMAC uses early warning alarms to dynamically adapt the sensing
intervals and communication periods of a sensor according to the likelihood of any
new events occurring. Results demonstrated that compared to previous protocols such
as SMAC, ADAMAC dramatically reduces end-to-end delay while still limiting energy
consumption during data collection and dissemination. The protocols developed in this thesis, DPPS and ADAMAC, effectively alleviate
the energy constraints associated with WSNs and will support the extension of sensorbased
networks to many more application areas than had hitherto been readily possible
Modelling and Evaluation of 60 GHz IEEE 802.11 Wireless Local Area Networks in ns-3
In this thesis we present modifications made to the popular network simulation environment ns-3 to provide accurate simulation of IEEE 802.11ad Wireless Local Area Networks (WLANs) in the 60 GHz band. There is a need for such a framework as it allows research into how a directional, high performance wireless link affects various parts of the networking stack and Medium Access Control (MAC) design.
The work contained herein describes changes made to the existing WLAN MAC and Physical Layer (PHY) model in ns-3 to support antenna directionality and multi-Gbps throughput. The resulting model is then analysed and found to accurately match optimal theoretical values in a number oftest scenarios.
The result of this work is a simulation model capable of emulating IEEE 802.11ad WLANs with correct MAC and PHY representations
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