274 research outputs found
Minimum mean-squared error iterative successive parallel arbitrated decision feedback detectors for DS-CDMA systems
In this paper we propose minimum mean squared error (MMSE) iterative successive parallel arbitrated decision feedback (DF) receivers for direct sequence code division multiple access (DS-CDMA) systems. We describe the MMSE design criterion for DF multiuser detectors along with successive, parallel and iterative interference cancellation structures. A novel efficient DF structure that employs successive cancellation with parallel arbitrated branches and a near-optimal low complexity user ordering algorithm are presented. The proposed DF receiver structure and the ordering algorithm are then combined with iterative cascaded DF stages for mitigating the deleterious effects of error propagation for convolutionally encoded systems with both Viterbi and turbo decoding as well as for uncoded schemes. We mathematically study the relations between the MMSE achieved by the analyzed DF structures, including the novel scheme, with imperfect and perfect feedback. Simulation results for an uplink scenario assess the new iterative DF detectors against linear receivers and evaluate the effects of error propagation of the new cancellation methods against existing ones
Adaptive DS-CDMA multiuser detection for time variant frequency selective Rayleigh fading channel
The current digital wireless mobile system such as IS-95, which is based on direct sequence Code Division Multiple Access (DS-CDMA) technology, will not be able to meet the growing demands for multimedia service due to low information exchanging rate. Its capacity is also limited by multiple accessed interference (MAI) signals.
This work focuses on the development of adaptive algorithms for multiuser detection (MUD) and interference suppression for wideband direct sequence code division multiple access (DS-CDMA) systems over time-variant frequency selective fading channels. In addition, channel acquisition and delay estimation techniques are developed to combat the uncertainty introduced by the wireless propagation channel. This work emphasizes fast and simple techniques that can meet practical needs for high data rate signal detection.
Most existing literature is not suitable for the large delay spread in wideband systems due to high computational/ hardware complexity. A de-biasing decorrelator is developed whose computational complexity is greatly reduced without sacrificing performance. An adaptive bootstrap symbolbased signal separator is also proposed for a time-variant channel. These detectors achieve MUD for asynchronous, large delay spread, fading channels without training sequences.
To achieve high data rate communication, a finite impulse response (FIR) filter based detector is presented for M-ary QAM modulated signals in a multipath Rayleigh fading channel. It is shown that the proposed detector provides a stable performance for QAM signal detection with unknown fading and phase shift. It is also shown that this detector can be easily extended to the reception of any M-ary quadrature modulated signal.
A minimum variance decorrelating (MVD) receiver with adaptive channel estimator is presented in this dissertation. It provides comparable performance to a linear MMSE receiver even in a deep fading environment and can be implemented blindly. Using the MVD receiver as a building-block, an adaptive multistage parallel interference cancellation (PIC) scheme and a successive interference cancellation (SIC) scheme were developed. The total number of stages is kept at a minimum as a result of the accurate estimating of the interfering users at the earliest stages, which reduces the implementation complexity, as well as the processing delay. Jointly with the MVD receiver, a new transmit diversity (TD) scheme, called TD-MVD, is proposed. This scheme improves the performance without increasing the bandwidth. Unlike other TD techniques, this TDMVD scheme has the inherent advantage to overcome asynchronous multipath transmission. It brings flexibility in the design of TD antenna systems without restrict signal coordination among those multiple transmissions, and applicable for both existing and next generation of CDMA systems.
A maximum likelihood based delay and channel estimation algorithm with reduced computational complexity is proposed. This algorithm uses a diagonal simplicity technique as well as the asymptotically uncorrelated property of the received signal in the frequency domain. In combination with oversampling, this scheme does not suffer from a singularity problem and the performance quickly approaches the Cramer-Rao lower bound (CRLB) while maintaining a computational complexity that is as low as the order of the signal dimension
High Capacity CDMA and Collaborative Techniques
The thesis investigates new approaches to increase the user capacity and improve the error
performance of Code Division Multiple Access (CDMA) by employing adaptive interference cancellation
and collaborative spreading and space diversity techniques. Collaborative Coding Multiple
Access (CCMA) is also investigated as a separate technique and combined with CDMA. The
advantages and shortcomings of CDMA and CCMA are analysed and new techniques for both the
uplink and downlink are proposed and evaluated.
Multiple access interference (MAI) problem in the uplink of CDMA is investigated first. The
practical issues of multiuser detection (MUD) techniques are reviewed and a novel blind adaptive
approach to interference cancellation (IC) is proposed. It exploits the constant modulus (CM)
property of digital signals to blindly suppress interference during the despreading process and obtain
amplitude estimation with minimum mean squared error for use in cancellation stages. Two
new blind adaptive receiver designs employing successive and parallel interference cancellation
architectures using the CM algorithm (CMA) referred to as ‘CMA-SIC’ and ‘BA-PIC’, respectively,
are presented. These techniques have shown to offer near single user performance for large
number of users. It is shown to increase the user capacity by approximately two fold compared
with conventional IC receivers. The spectral efficiency analysis of the techniques based on output
signal-to interference-and-noise ratio (SINR) also shows significant gain in data rate. Furthermore,
an effective and low complexity blind adaptive subcarrier combining (BASC) technique using a
simple gradient descent based algorithm is proposed for Multicarrier-CDMA. It suppresses MAI
without any knowledge of channel amplitudes and allows large number of users compared with
equal gain and maximum ratio combining techniques normally used in practice.
New user collaborative schemes are proposed and analysed theoretically and by simulations
in different channel conditions to achieve spatial diversity for uplink of CCMA and CDMA. First,
a simple transmitter diversity and its equivalent user collaborative diversity techniques for CCMA
are designed and analysed. Next, a new user collaborative scheme with successive interference
cancellation for uplink of CDMA referred to as collaborative SIC (C-SIC) is investigated to reduce
MAI and achieve improved diversity. To further improve the performance of C-SIC under high
system loading conditions, Collaborative Blind Adaptive SIC (C-BASIC) scheme is proposed.
It is shown to minimize the residual MAI, leading to improved user capacity and a more robust
system. It is known that collaborative diversity schemes incur loss in throughput due to the need of
orthogonal time/frequency slots for relaying source’s data. To address this problem, finally a novel
near-unity-rate scheme also referred to as bandwidth efficient collaborative diversity (BECD) is proposed and evaluated for CDMA. Under this scheme, pairs of users share a single spreading sequence to exchange and forward their data employing a simple superposition or space-time
encoding methods. At the receiver collaborative joint detection is performed to separate each
paired users’ data. It is shown that the scheme can achieve full diversity gain at no extra bandwidth
as inter-user channel SNR becomes high.
A novel approach of ‘User Collaboration’ is introduced to increase the user capacity of CDMA
for both the downlink and uplink. First, collaborative group spreading technique for the downlink
of overloaded CDMA system is introduced. It allows the sharing of the same single spreading
sequence for more than one user belonging to the same group. This technique is referred to as
Collaborative Spreading CDMA downlink (CS-CDMA-DL). In this technique T-user collaborative
coding is used for each group to form a composite codeword signal of the users and then a
single orthogonal sequence is used for the group. At each user’s receiver, decoding of composite
codeword is carried out to extract the user’s own information while maintaining a high SINR performance.
To improve the bit error performance of CS-CDMA-DL in Rayleigh fading conditions,
Collaborative Space-time Spreading (C-STS) technique is proposed by combining the collaborative
coding multiple access and space-time coding principles. A new scheme for uplink of CDMA
using the ‘User Collaboration’ approach, referred to as CS-CDMA-UL is presented next. When
users’ channels are independent (uncorrelated), significantly higher user capacity can be achieved
by grouping multiple users to share the same spreading sequence and performing MUD on per
group basis followed by a low complexity ML decoding at the receiver. This approach has shown
to support much higher number of users than the available sequences while also maintaining the
low receiver complexity. For improved performance under highly correlated channel conditions,
T-user collaborative coding is also investigated within the CS-CDMA-UL system
Correcting the Bias of Subtractive Interference Cancellation in CDMA: Advanced Mean Field Theory
In this paper we introduce an advanced mean field method to correct the inherent bias of conventional subtractive interference cancellation in Code Division Multiple Access (CDMA). In simulations, we get a performance quite close to that of the individual optimal exponential complexity detector and significant improvements over current state-of-the-art subtractive interference cancellation in all setups tested, for example in one case doubling the number of user at a bit error rate of. To obtain such a good performance for finite size systems, where the performance is normally degraded by the presence of suboptimal fix-point solutions, it is crucial to use the method in conjunction with mean field annealing, i.e. solving the fixed point equations at decreasing temperatures (noise levels). In the limit of infinite large system size, the new subtractive interference cancellation scheme is expected to be identical to the individual optimal detector. The computational complexity is cubic in the number of users whereas conventional (naive mean field) subtractive interference cancellation is quadratic. We also present a quadratic complexity approximation to our new method that also gives performance improvements, but in addition requires knowledge of the spreading code statistics. The proposed methodology is quite general and is expected to be applicable to other digital communication problems
Multi-Step Knowledge-Aided Iterative ESPRIT for Direction Finding
In this work, we propose a subspace-based algorithm for DOA estimation which
iteratively reduces the disturbance factors of the estimated data covariance
matrix and incorporates prior knowledge which is gradually obtained on line. An
analysis of the MSE of the reshaped data covariance matrix is carried out along
with comparisons between computational complexities of the proposed and
existing algorithms. Simulations focusing on closely-spaced sources, where they
are uncorrelated and correlated, illustrate the improvements achieved.Comment: 7 figures. arXiv admin note: text overlap with arXiv:1703.1052
Adaptive and Iterative Multi-Branch MMSE Decision Feedback Detection Algorithms for MIMO Systems
In this work, decision feedback (DF) detection algorithms based on multiple
processing branches for multi-input multi-output (MIMO) spatial multiplexing
systems are proposed. The proposed detector employs multiple cancellation
branches with receive filters that are obtained from a common matrix inverse
and achieves a performance close to the maximum likelihood detector (MLD).
Constrained minimum mean-squared error (MMSE) receive filters designed with
constraints on the shape and magnitude of the feedback filters for the
multi-branch MMSE DF (MB-MMSE-DF) receivers are presented. An adaptive
implementation of the proposed MB-MMSE-DF detector is developed along with a
recursive least squares-type algorithm for estimating the parameters of the
receive filters when the channel is time-varying. A soft-output version of the
MB-MMSE-DF detector is also proposed as a component of an iterative detection
and decoding receiver structure. A computational complexity analysis shows that
the MB-MMSE-DF detector does not require a significant additional complexity
over the conventional MMSE-DF detector, whereas a diversity analysis discusses
the diversity order achieved by the MB-MMSE-DF detector. Simulation results
show that the MB-MMSE-DF detector achieves a performance superior to existing
suboptimal detectors and close to the MLD, while requiring significantly lower
complexity.Comment: 10 figures, 3 tables; IEEE Transactions on Wireless Communications,
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