425 research outputs found
Large-Scale MIMO versus Network MIMO for Multicell Interference Mitigation
This paper compares two important downlink multicell interference mitigation
techniques, namely, large-scale (LS) multiple-input multiple-output (MIMO) and
network MIMO. We consider a cooperative wireless cellular system operating in
time-division duplex (TDD) mode, wherein each cooperating cluster includes
base-stations (BSs), each equipped with multiple antennas and scheduling
single-antenna users. In an LS-MIMO system, each BS employs antennas not
only to serve its scheduled users, but also to null out interference caused to
the other users within the cooperating cluster using zero-forcing (ZF)
beamforming. In a network MIMO system, each BS is equipped with only
antennas, but interference cancellation is realized by data and channel state
information exchange over the backhaul links and joint downlink transmission
using ZF beamforming. Both systems are able to completely eliminate
intra-cluster interference and to provide the same number of spatial degrees of
freedom per user. Assuming the uplink-downlink channel reciprocity provided by
TDD, both systems are subject to identical channel acquisition overhead during
the uplink pilot transmission stage. Further, the available sum power at each
cluster is fixed and assumed to be equally distributed across the downlink
beams in both systems. Building upon the channel distribution functions and
using tools from stochastic ordering, this paper shows, however, that from a
performance point of view, users experience better quality of service, averaged
over small-scale fading, under an LS-MIMO system than a network MIMO system.
Numerical simulations for a multicell network reveal that this conclusion also
holds true with regularized ZF beamforming scheme. Hence, given the likely
lower cost of adding excess number of antennas at each BS, LS-MIMO could be the
preferred route toward interference mitigation in cellular networks.Comment: 13 pages, 7 figures; IEEE Journal of Selected Topics in Signal
Processing, Special Issue on Signal Processing for Large-Scale MIMO
Communication
Optimal Channel Training in Uplink Network MIMO Systems
We consider a multi-cell frequency-selective fading uplink channel (network
MIMO) from K single-antenna user terminals (UTs) to B cooperative base stations
(BSs) with M antennas each. The BSs, assumed to be oblivious of the applied
codebooks, forward compressed versions of their observations to a central
station (CS) via capacity limited backhaul links. The CS jointly decodes the
messages from all UTs. Since the BSs and the CS are assumed to have no prior
channel state information (CSI), the channel needs to be estimated during its
coherence time. Based on a lower bound of the ergodic mutual information, we
determine the optimal fraction of the coherence time used for channel training,
taking different path losses between the UTs and the BSs into account. We then
study how the optimal training length is impacted by the backhaul capacity.
Although our analytical results are based on a large system limit, we show by
simulations that they provide very accurate approximations for even small
system dimensions.Comment: 15 pages, 7 figures. To appear in the IEEE Transactions on Signal
Processin
Mathematical optimization and game theoretic techniques for multicell beamforming
The main challenge in mobile wireless communications is the incompatibility between limited wireless resources and increasing demand on wireless services. The employment of frequency reuse technique has effectively increased the capacity of the network and improved the efficiency of frequency utilization. However, with the emergence of smart phones and even more data hungry applications such as interactive multimedia, higher data rate is demanded by mobile users. On the other hand, the interference induced by
spectrum sharing arrangement has severely degraded the quality of service for users and restricted further reduction of cell size and enhancement of frequency reuse factor.
Beamforming technique has great potential to improve the network performance. With the employment of multiple antennas, a base station is capable of directionally transmitting signals to desired users through narrow beams rather than omnidirectional waves. This will result users suffer less interference from the signals transmitted to other co-channel users. In addition, with the combination of beamforming technique and appropriate power control schemes, the resources of the wireless networks can be used more efficiently.
In this thesis, mathematical optimization and game theoretic techniques have been exploited for beamforming designs within the context of multicell
wireless networks. Both the coordinated beamforming and the coalitional game theoretic based beamforming techniques have been proposed. Initially, coordinated multicell beamforming algorithms for mixed design criteria have been developed, in which some users are allowed to achieve target signal-to-interference-
plus-noise ratios (SINRs) while the SINRs of rest of the users in all cells will be balanced to a maximum achievable SINR. An SINR balancing based coordinated multicell beamforming algorithm has then been proposed which is capable of balancing users in different cells to different SINR levels. Finally, a coalitional game based multicell beamforming has been considered, in which the proposed coalition formation algorithm can reach to stable coalition structures. The performances of all the proposed algorithms have been demonstrated using MATLAB based simulations
Joint Beamforming and Power Control in Coordinated Multicell: Max-Min Duality, Effective Network and Large System Transition
This paper studies joint beamforming and power control in a coordinated
multicell downlink system that serves multiple users per cell to maximize the
minimum weighted signal-to-interference-plus-noise ratio. The optimal solution
and distributed algorithm with geometrically fast convergence rate are derived
by employing the nonlinear Perron-Frobenius theory and the multicell network
duality. The iterative algorithm, though operating in a distributed manner,
still requires instantaneous power update within the coordinated cluster
through the backhaul. The backhaul information exchange and message passing may
become prohibitive with increasing number of transmit antennas and increasing
number of users. In order to derive asymptotically optimal solution, random
matrix theory is leveraged to design a distributed algorithm that only requires
statistical information. The advantage of our approach is that there is no
instantaneous power update through backhaul. Moreover, by using nonlinear
Perron-Frobenius theory and random matrix theory, an effective primal network
and an effective dual network are proposed to characterize and interpret the
asymptotic solution.Comment: Some typos in the version publised in the IEEE Transactions on
Wireless Communications are correcte
Enabling Technology and Algorithm Design for Location-Aware Communications
Location-awareness is emerging as a promising technique for future-generation wire less network to adaptively enhance and optimize its overall performance through location-enabled technologies such as location-assisted transceiver reconfiguration and routing. The availability of accurate location information of mobile users becomes the essential prerequisite for the design of such location-aware networks. Motivated by the low locationing accuracy of the Global Positioning System (GPS) in dense multipath environments, which is commonly used for acquiring location information in most of the existing wireless networks, wireless communication system-based positioning systems have been investigated as alternatives to fill the gap of the GPS in coverage. Distance-based location techniques using time-of-arrival (TOA) measurements are commonly preferred by broadband wireless communications where the arrival time of the signal component of the First Arriving Path (FAP) can be converted to the distance between the receiver and the transmitter with known location. With at least three transmitters, the location of the receiver can be determined via trilatération method. However, identification of the FAP’s signal component in dense multipath scenarios is quite challenging due to the significantly weaker power of the FAP as compared with the Later Arriving Paths (LAPs) from scattering, reflection and refraction, and the superposition of these random arrival LAPs’ signal compo nents will become large interference to detect the FAP. In this thesis, a robust FAP detection scheme based on multipath interference cancellation is proposed to im prove the accuracy of location estimation in dense multipath environments. In the proposed algorithm, the signal components of LAPs is reconstructed based on the estimated channel and data with the assist of the communication receiver, and sub sequently removed from the received signal. Accurate FAP detection results are then achieved with the cross-correlation between the interference-suppressed signal and an augmented preamble which is the combination of the original preamble for com munications and the demodulated data sequences. Therefore, more precise distance estimation (hence location estimation) can be obtained with the proposed algorithm for further reliable network optimization strategy design.
On the other hand, multiceli cooperative communication is another emerging technique to substantially improve the coverage and throughput of traditional cellular networks. Location-awareness also plays an important role in the design and implementation of multiceli cooperation technique. With accurate location information of mobile users, the complexity of multiceli cooperation algorithm design can be dramatically reduced by location-assisted applications, e.g., automatic cooperative base station (BS) determination and signal synchronization. Therefore, potential latency aroused by cooperative processing will be minimized. Furthermore, the cooperative BSs require the sharing of certain information, e.g., channel state information (CSI), user data and transmission parameters to perform coordination in their signaling strategies. The BSs need to have the capabilities to exchange available information with each other to follow up with the time-varying communication environment. As most of broadband wireless communication systems are already orthogonal frequency division multiplexing (OFDM)-based, a Multi-Layered OFDM System, which is specially tailored for multiceli cooperation is investigated to provide parallel robust, efficient and flexible signaling links for BS coordination purposes. These layers are overlaid with data-carrying OFDM signals in both time and frequency domains and therefore, no dedicated radio resources are required for multiceli cooperative networks.
In the final aspect of this thesis, an enhanced channel estimation through itera tive decision-directed method is investigated for OFDM system, which aims to provide more accurate estimation results with the aid of the demodulated OFDM data. The performance of traditional training sequence-based channel estimation is often lim ited by the length of the training. To achieve acceptable estimation performance, a long sequence has to be used which dramatically reduces the transmission efficiency of data communication. In this proposed method, the restriction of the training sequence length can be removed and high channel estimation accuracy can be achieved with high transmission efficiency, and therefore it particular fits in multiceli cooperative networks. On the other hand, as the performance of the proposed FAP detection scheme also relies on the accuracy of channel estimation and data detection results, the proposed method can be combined with the FAP detection scheme to further optimize the accuracy of multipath interference cancellation and FAP detection
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