| 1. |
- Čirkić, Mirsad, 1984-, et al.
(författare)
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Allocation of Computational Resources for Soft MIMO Detection
- 2011
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Ingår i: IEEE Journal of Selected Topics in Signal Processing. - : IEEE conference proceedings. - 1932-4553. ; 5:8, s. 1451-1461
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Tidskriftsartikel (refereegranskat)abstract
- We consider soft MIMO detection for the case of block fading. That is, the transmitted codeword spans over several independent channel realizations and several instances of the detection problem must be solved for each such realization. We develop methods that adaptively allocate computational resources to the detection problems of each channel realization, under a total per-codeword complexity constraint. Our main results are a formulation of the problem as a mathematical optimization problem with a well-defined objective function and constraints, and algorithms that solve this optimization problem efficiently computationally.
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| 2. |
- Čirkić, Mirsad, 1984-, et al.
(författare)
-
Gaussian Approximation of the LLR Distribution for the ML and Partial Marginalization MIMO detectors
- 2011
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Ingår i: Proceedings of the IEEE International Conference on Acoustics, Speech and SignalProcessing (ICASSP). - : IEEE conference proceedings. - 9781457705373 ; , s. 3232-3235
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Konferensbidrag (refereegranskat)abstract
- We derive a Gaussian approximation of the LLR distribution conditioned on the transmitted signal and the channel matrix for the soft-output via partial marginalization MIMO detector. This detector performs exact ML as a special case. Our main results consist of discussing the operational meaning of this approximation and a proof that, in the limit of high SNR, the LLR distribution of interest converges in probability towards a Gaussian distribution.
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| 3. |
- Čirkić, Mirsad, 1984-, et al.
(författare)
-
Near-Optimal Soft-Output Fixed-Complexity MIMO Detection via Subspace Marginalization and Interference Suppression
- 2012
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Ingår i: 2012 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP). - : IEEE Signal Processing Society. - 9781467300445 - 9781467300452 ; , s. 2805-2808
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Konferensbidrag (refereegranskat)abstract
- The fundamental problem of our interest here is soft MIMO detection. We propose a method that yields excellent performance, atlow and at fixed (deterministic) complexity. Our method provides a well-defined tradeoff between computational complexity and performance. Apart from an initial step consisting of selecting columns,the algorithm involves no searching nor algorithmic branching; hence the algorithm has a completely predictable run-time, and it is readily and massively parallelizable.
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| 4. |
- Čirkić, Mirsad, 1984-, et al.
(författare)
-
New Results on Adaptive Computational Resource Allocation in Soft MIMO Detection
- 2011
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Ingår i: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). - : IEEE conference proceedings. ; , s. 2972-2975
-
Konferensbidrag (refereegranskat)abstract
- The fundamental problem of our interest is soft MIMO detection for the case of block fading, i.e., when the transmitted codeword spans over several independent channel realizations. We develop methods that adaptively allocate computational resources to the detection problems of each channel realization, under a total per-codeword complexity constraint. The new results consist of a new algorithm, a new performance measure, and a thorough complexity discussion.
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| 5. |
- Čirkić, Mirsad, 1984-, et al.
(författare)
-
On the Complexity of Very Large Multi-User MIMO Detection
- 2014
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Ingår i: 2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), IEEE. - : IEEE Press. - 9781479949038 ; , s. 55-59
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Konferensbidrag (refereegranskat)abstract
- This work discusses efficient techniques for detection in large-size multi-user multiple-input multiple-output (MIMO) systems that are highly overdetermined. We exemplify the application of conjugate gradient methods in the setup of our interest and compare its performance with respect to methods based on the Neumann series expansion. We bring to light some important insights on the performance versus complexity tradeoffs that have not been uplifted before.
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| 6. |
- Čirkić, Mirsad, 1984-
(författare)
-
Optimization of Computational Resources for MIMO Detection
- 2011
-
Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- For the past decades, the demand in transferring large amounts of data rapidly and reliably has been increasing drastically. One of the more promising techniques that can provide the desired performance is the multiple-input multiple-output (MIMO) technology where multiple antennas are placed at both the transmitting and receiving side of the communication link. One major implementation difficulty of the MIMO technology is the signal separation (detection) problem at the receiving side of the MIMO link. This is due to the fact that the transmitted signals interfere with each other and that separating them can be very difficult if the MIMO channel conditions are not beneficial, i.e., the channel is not well-conditioned.For well-conditioned channels, low-complexity detection methods are often sufficiently accurate. In such cases, performing computationally very expensive optimal detection would be a waste of computational power. This said, for MIMO detection in a coded system, there is always a trade-off between performance and complexity. The fundamental question is, can we save computational resources by performing optimal detection only when it is needed, and something simpler when it is not? This is the question that this thesis aims to answer. In doing so, we present a general framework for adaptively allocating computational resources to different (“simple” and“difficult”) detection problems. This general framework is applicable to any MIMO detector and scenario of choice, and it is exemplified using one particular detection method for which specific allocation techniques are developed and evaluated.
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| 7. |
- Čirkić, Mirsad, 1984-, et al.
(författare)
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SUMIS: Near-Optimal Soft-In Soft-Out MIMO Detection with Low and Fixed Complexity
- 2014
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Ingår i: IEEE Transactions on Signal Processing. - : IEEE Signal Processing Society. - 1053-587X .- 1941-0476. ; 62:12, s. 3084-3097
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Tidskriftsartikel (refereegranskat)abstract
- The fundamental problem of interest here is soft-input soft-output multiple-input multiple-output (MIMO) detection. We propose a method, referred to as subspace marginalization with interference suppression (SUMIS), that yields unprecedented performance at low and fixed (deterministic) complexity. Our method provides a well-defined tradeoff between computational complexity and performance. Apart from an initial sorting step consisting of selecting channel-matrix columns, the algorithm involves no searching nor algorithmic branching; hence the algorithm has a completely predictable run-time and allows for a highly parallel implementation. We numerically assess the performance of SUMIS in different practical settings: full/partial channel state information, sequential/iterative decoding, and low/high rate outer codes. We also comment on how the SUMIS method performs in systems with a large number of transmit antennas.
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