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- Brandt, Rasmus, 1985-
(författare)
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Distributed Coordination in Multiantenna Cellular Networks
- 2016
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Wireless communications are important in our highly connected world. The amount of data being transferred in cellular networks is steadily growing, and consequently more capacity is needed. This thesis considers the problem of downlink capacity improvement from the perspective of multicell coordination. By employing multiple antennas at the transmitters and receivers of a multicell network, the inherent spatial selectivity of the users can be exploited in order to increase the capacity through linear precoding and receive filtering. For the coordination between cells, distributed algorithms are often sought due to their low implementation complexity and robustness. In this context, the thesis considers two problem domains: base station clustering and coordinated precoding.Base station clustering corresponds to grouping the cell base stations into disjoint clusters in order to reduce the coordination overhead. This is needed in intermediate-sized to large networks, where the overhead otherwise would be overwhelmingly high. Two solution methods for the clustering problem are proposed: an optimal centralized method, as well as a heuristic distributed method. The optimal method applies to a family of throughput models and exploits the structure of the model to find bounds that can be used to focus the search for the optimal clustering into promising territories. The distributed method instead uses notions from coalitional game theory, where the base stations are modelled as rational and intelligent players in a game. By letting the players make individual deviations that benefit them in the game, i.e.\@ switching clusters, a distributed coalition formation algorithm is obtained.Coordinated precoding is the act of finding the linear precoders and receive filters that maximize the network performance, given a base station clustering. Four specific challenges are studied in this problem domain. First, coordinated precoding under intercluster interference is considered. The channels of the intercluster links are not explicitly estimated due to overhead reasons, and these links thus lead to intercluster interference. By exploiting the known statistics of the intercluster channels, a robust and distributed coordinated precoding algorithm is developed. Second, coordinated precoding under imperfect channel state information is considered. Relying on the channel reciprocity under time-division duplex operation, a distributed estimation framework is proposed. Given the estimated channels, a robust and distributed coordinated precoding algorithm is then derived. Third, coordinated precoding under imperfect radio hardware is considered. By modelling the radio frequency distortion noises, a distributed coordinated precoding method that accounts for the imperfections is proposed. Fourth, joint coordinated precoding and discrete rate selection is considered. By bounding and linearizing an originally intractable optimization problem, a heuristic algorithm is derived which selects the transmit rate from a finite set and simultaneously forms the linear precoders and receive filters.
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| 2. |
- Brandt, Rasmus, 1985-, et al.
(författare)
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Distributed CSI Acquisition and Coordinated Precoding for TDD Multicell MIMO Systems
- 2016
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Ingår i: IEEE Transactions on Vehicular Technology. - : IEEE Press. - 0018-9545 .- 1939-9359. ; 65:5, s. 2890-2906
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Tidskriftsartikel (refereegranskat)abstract
- Several distributed coordinated precoding methods exist in the downlink multicell MIMO literature, many of which assume perfect knowledge of received signal covariance and local effective channels. In this work, we let the notion of channel state information (CSI) encompass this knowledge of covariances and effective channels. We analyze what local CSI is required in the WMMSE algorithm for distributed coordinated precoding, and study how this required CSI can be obtained in a distributed fashion. Based on pilot-assisted channel estimation, we propose three CSI acquisition methods with different tradeoffs between feedback and signaling, backhaul use, and computational complexity. One of the proposed methods is fully distributed, meaning that it only depends on over-the-air signaling but requires no backhaul, and results in a fully distributed joint system when coupled with the WMMSE algorithm. Naively applying the WMMSE algorithm together with the fully distributed CSI acquisition results in catastrophic performance however, and therefore we propose a robustified WMMSE algorithm based on the well known diagonal loading framework. By enforcing properties of the WMMSE solutions with perfect CSI onto the problem with imperfect CSI, the resulting diagonally loaded spatial filters are shown to perform significantly better than the naive filters. The proposed robust and distributed system is evaluated using numerical simulations, and shown to perform well compared with benchmarks. Under centralized CSI acquisition, the proposed algorithm performs on par with other existing centralized robust WMMSE algorithms. When evaluated in a large scale fading environment, the performance of the proposed system is promising.
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| 3. |
- Brandt, Rasmus, 1985-, et al.
(författare)
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Distributed Long-Term Base Station Clustering in Cellular Networks using Coalition Formation
- 2016
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Ingår i: IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS. - : IEEE. - 2373-776X. ; 2:3
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Tidskriftsartikel (refereegranskat)abstract
- Interference alignment (IA) is a promising technique for interference mitigation in multicell networks due to its ability to completely cancel the intercell interference through linear precoding and receive filtering. In small networks, the amount of required channel state information (CSI) is modest and IA is therefore typically applied jointly over all base stations. In large networks, where the channel coherence time is short in comparison to the time needed to obtain the required CSI, base station clustering must be applied however. We model such clustered multicell networks as a set of coalitions, where CSI acquisition and IA precoding is performed independently within each coalition. We develop a long-term throughput model which includes both CSI acquisition overhead and the level of interference mitigation ability as a function of the coalition structure. Given the throughput model, we formulate a coalitional game where the involved base stations are the rational players. Allowing for individual deviations by the players, we formulate a distributed coalition formation algorithm with low complexity and low communication overhead that leads to an individually stable coalition structure. The dynamic clustering is performed using only long-term CSI, but we also provide a robust short-term precoding algorithm which accounts for the intercoalition interference when spectrum sharing is applied between coalitions. Numerical simulations show that the distributed coalition formation is generally able to reach long-term sum throughputs within 10 % of the global optimum.
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| 4. |
- Brandt, Rasmus, 1985-, et al.
(författare)
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Globally Optimal Base Station Clustering in Interference Alignment-Based Multicell Networks
- 2016
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Ingår i: IEEE Signal Processing Letters. - : IEEE. - 1070-9908 .- 1558-2361. ; 23:4, s. 512-516
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Tidskriftsartikel (refereegranskat)abstract
- Coordinated precoding based on interference alignment is a promising technique for improving the throughputs in future wireless multicell networks. In small networks, all base stations can typically jointly coordinate their precoding. In large networks however, base station clustering is necessary due to the otherwise overwhelmingly high channel state information (CSI) acquisition overhead. In this work, we provide a branch and bound algorithm for finding the globally optimal base station clustering. The algorithm is mainly intended for benchmarking existing suboptimal clustering schemes. We propose a general model for the user throughputs, which only depends on the long-term CSI statistics. The model assumes intracluster interference alignment and is able to account for the CSI acquisition overhead. By enumerating a search tree using a best-first search and pruning sub-trees in which the optimal solution provably cannot be, the proposed method converges to the optimal solution. The pruning is done using specifically derived bounds, which exploit some assumed structure in the throughput model. It is empirically shown that the proposed method has an average complexity which is orders of magnitude lower than that of exhaustive search.
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