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In this work, we consider spectrum sensing of OFDM signals. We deal withthe inevitable problem of a carrier frequency offset, and propose modificationsto some state-of-the-art detectors to cope with that. Moreover, the (modified)detectors are implemented using GNU radio and USRP, and evaluated over aphysical radio channel. Measurements show that all of the evaluated detectorsperform quite well, and the preferred choice of detector depends on thedetection requirements and the radio environment.

We consider the uplink of multicell multiuser MIMO(MU-MIMO) systems with very large antenna arrays at the base station (BS). We assume that the BS estimates the channel through uplink training, and then uses this channel estimate to detect the signals transmitted from a multiplicity of autonomous users in its cell. By taking the correlation between the channel estimate and the interference from other cells into account, we propose an optimal linear receiver (OLR) which maximizes the received signal-to-interference-plus-noise (SINR). Analytical approximations of the exact and lower bound on the achievable rate are then derived. The bound is very tight, especially at large number of BS antennas. We show that at low SINR, maximal-ratio combing (MRC) receiver performs as well as OLR, however at high SINR, OLR outperforms MRC. Compared with the typical minimum mean-square error receiver, our proposed OLR improves systematically the system performance, especially when the interference is large.

We consider the joint allocation of receiver, bit, and power to subcarriers in the downlink of multicell orthogonal frequency-division multiple-access (OFDMA) networks. Assuming that the cells share the entire bandwidth and that the rates are discrete, we formulate the joint allocation problem as a nonlinear mixed integer program (MIP), which however has exponential worst-case complexity. We capitalize on the capability of the receivers to measure the interference-plus-noise on every subcarrier and decompose the joint problem into a set of smaller-scale linear MIPs solved by individual base stations. Accordingly, we propose a distributed algorithm with linear complexity, in which the base stations participate in the problem solution in a round-robin manner. Simulation results demonstrate the effectiveness of the proposed algorithm in comparison with the iterative waterfilling algorithm and the successive optimal solution, by means of standard branch-and-cut solvers, of the individual MIPs.

In this work, we consider spectrum sensing of OFDM signals. We deal withthe inevitable problem of a carrier frequency offset, and propose modificationsto some state-of-the-art detectors to cope with that. Moreover, the (modified)detectors are implemented using GNU radio and USRP, and evaluated over aphysical radio channel. Measurements show that all of the evaluated detectorsperform quite well, and the preferred choice of detector depends on thedetection requirements and the radio environment.

We consider the joint allocation of receiver, bit, and power to subcarriers in the downlink of multicell orthogonal frequency-division multiple-access (OFDMA) networks. Assuming that the cells share the entire bandwidth and that the rates are discrete, we formulate the joint allocation problem as a nonlinear mixed integer program (MIP), which however has exponential worst-case complexity. We capitalize on the capability of the receivers to measure the interference-plus-noise on every subcarrier and decompose the joint problem into a set of smaller-scale linear MIPs solved by individual base stations. Accordingly, we propose a distributed algorithm with linear complexity, in which the base stations participate in the problem solution in a round-robin manner. Simulation results demonstrate the effectiveness of the proposed algorithm in comparison with the iterative waterfilling algorithm and the successive optimal solution, by means of standard branch-and-cut solvers, of the individual MIPs.

In this work, we consider spectrum sensing of OFDM signals. We deal withthe inevitable problem of a carrier frequency offset, and propose modificationsto some state-of-the-art detectors to cope with that. Moreover, the (modified)detectors are implemented using GNU radio and USRP, and evaluated over aphysical radio channel. Measurements show that all of the evaluated detectorsperform quite well, and the preferred choice of detector depends on thedetection requirements and the radio environment.

The effect of oscillator phase noise on the sumrate performance of a frequency selective multi-user multipleinputmultiple-output (MU-MIMO) uplink channel is studiedunder imperfect channel state information. A maximum ratiocombining detection strategy is employed by the base station(BS) (having a large antenna array of M elements), and ananalytical expression of a lower bound on the sum capacity ofthe system is derived. It is shown that an array power gainof O(pM) is achievable. It is also observed that phase noiseeffectively limits the fraction of the time used for informationtransmission and the number of users in the system. Finally itis concluded that, phase noise degrades the performance butdoes not eliminate the fundamental gains of a Large ScaleAntenna System (LSAS), i.e., power efficiency and high sumrate performance with low complexity receiver processing.

The effect of oscillator phase noise on the sumrate performance of a frequency selective multi-user multipleinputmultiple-output (MU-MIMO) uplink channel is studiedunder imperfect channel state information. A maximum ratiocombining detection strategy is employed by the base station(BS) (having a large antenna array of M elements), and ananalytical expression of a lower bound on the sum capacity ofthe system is derived. It is shown that an array power gainof O(pM) is achievable. It is also observed that phase noiseeffectively limits the fraction of the time used for informationtransmission and the number of users in the system. Finally itis concluded that, phase noise degrades the performance butdoes not eliminate the fundamental gains of a Large ScaleAntenna System (LSAS), i.e., power efficiency and high sumrate performance with low complexity receiver processing.

The effect of oscillator phase noise on the sumrate performance of a frequency selective multi-user multipleinputmultiple-output (MU-MIMO) uplink channel is studiedunder imperfect channel state information. A maximum ratiocombining detection strategy is employed by the base station(BS) (having a large antenna array of M elements), and ananalytical expression of a lower bound on the sum capacity ofthe system is derived. It is shown that an array power gainof O(pM) is achievable. It is also observed that phase noiseeffectively limits the fraction of the time used for informationtransmission and the number of users in the system. Finally itis concluded that, phase noise degrades the performance butdoes not eliminate the fundamental gains of a Large ScaleAntenna System (LSAS), i.e., power efficiency and high sumrate performance with low complexity receiver processing.

In this work, we consider spectrum sensing of OFDM signals. We deal withthe inevitable problem of a carrier frequency offset, and propose modificationsto some state-of-the-art detectors to cope with that. Moreover, the (modified)detectors are implemented using GNU radio and USRP, and evaluated over aphysical radio channel. Measurements show that all of the evaluated detectorsperform quite well, and the preferred choice of detector depends on thedetection requirements and the radio environment.

We consider the joint allocation of receiver, bit, and power to subcarriers in the downlink of multicell orthogonal frequency-division multiple-access (OFDMA) networks. Assuming that the cells share the entire bandwidth and that the rates are discrete, we formulate the joint allocation problem as a nonlinear mixed integer program (MIP), which however has exponential worst-case complexity. We capitalize on the capability of the receivers to measure the interference-plus-noise on every subcarrier and decompose the joint problem into a set of smaller-scale linear MIPs solved by individual base stations. Accordingly, we propose a distributed algorithm with linear complexity, in which the base stations participate in the problem solution in a round-robin manner. Simulation results demonstrate the effectiveness of the proposed algorithm in comparison with the iterative waterfilling algorithm and the successive optimal solution, by means of standard branch-and-cut solvers, of the individual MIPs.

The effect of oscillator phase noise on the sumrate performance of a frequency selective multi-user multipleinputmultiple-output (MU-MIMO) uplink channel is studiedunder imperfect channel state information. A maximum ratiocombining detection strategy is employed by the base station(BS) (having a large antenna array of M elements), and ananalytical expression of a lower bound on the sum capacity ofthe system is derived. It is shown that an array power gainof O(pM) is achievable. It is also observed that phase noiseeffectively limits the fraction of the time used for informationtransmission and the number of users in the system. Finally itis concluded that, phase noise degrades the performance butdoes not eliminate the fundamental gains of a Large ScaleAntenna System (LSAS), i.e., power efficiency and high sumrate performance with low complexity receiver processing.

A multiplicity of autonomous terminals simultaneously transmits data streams to a compact array of antennas. The array uses imperfect channel-state information derived from transmitted pilots to extract the individual data streams. The power radiated by the terminals can be made inversely proportional to the square-root of the number of base station antennas with no reduction in performance. In contrast if perfect channel-state information were available the power could be made inversely proportional to the number of antennas. A maximum-ratio combining receiver normally performs worse than a zero-forcing receiver. However as power levels are reduced, the cross-talk introduced by the inferior maximum-ratio receiver eventually falls below the noise level and this simple receiver becomes a viable option.

We present a fast mechanism for determining which channel code that was used on a communication link. In the proposed scheme, the receiver does not need to receive the entire data to determine the actual code. Moreover, the proposed scheme can also be used to determine the interleaving/scrambling sequence that was used at the transmitter. We investigate the performance of the scheme for some standard convolutional codes., ©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Reza Moosavi and Erik G. Larsson, A Fast Scheme for Blind Identification of Channel Codes, 2011, accepted The 54th IEEE Global Communications Conference (GLOBECOM).

A multiplicity of autonomous terminals simultaneously transmits data streams to a compact array of antennas. The array uses imperfect channel-state information derived from transmitted pilots to extract the individual data streams. The power radiated by the terminals can be made inversely proportional to the square-root of the number of base station antennas with no reduction in performance. In contrast if perfect channel-state information were available the power could be made inversely proportional to the number of antennas. A maximum-ratio combining receiver normally performs worse than a zero-forcing receiver. However as power levels are reduced, the cross-talk introduced by the inferior maximum-ratio receiver eventually falls below the noise level and this simple receiver becomes a viable option.

A multiplicity of autonomous terminals simultaneously transmits data streams to a compact array of antennas. The array uses imperfect channel-state information derived from transmitted pilots to extract the individual data streams. The power radiated by the terminals can be made inversely proportional to the square-root of the number of base station antennas with no reduction in performance. In contrast if perfect channel-state information were available the power could be made inversely proportional to the number of antennas. A maximum-ratio combining receiver normally performs worse than a zero-forcing receiver. However as power levels are reduced, the cross-talk introduced by the inferior maximum-ratio receiver eventually falls below the noise level and this simple receiver becomes a viable option.

A multiplicity of autonomous terminals simultaneously transmits data streams to a compact array of antennas. The array uses imperfect channel-state information derived from transmitted pilots to extract the individual data streams. The power radiated by the terminals can be made inversely proportional to the square-root of the number of base station antennas with no reduction in performance. In contrast if perfect channel-state information were available the power could be made inversely proportional to the number of antennas. A maximum-ratio combining receiver normally performs worse than a zero-forcing receiver. However as power levels are reduced, the cross-talk introduced by the inferior maximum-ratio receiver eventually falls below the noise level and this simple receiver becomes a viable option.

We present a fast mechanism for determining which channel code that was used on a communication link. In the proposed scheme, the receiver does not need to receive the entire data to determine the actual code. Moreover, the proposed scheme can also be used to determine the interleaving/scrambling sequence that was used at the transmitter. We investigate the performance of the scheme for some standard convolutional codes., ©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Reza Moosavi and Erik G. Larsson, A Fast Scheme for Blind Identification of Channel Codes, 2011, accepted The 54th IEEE Global Communications Conference (GLOBECOM).

We present a fast mechanism for determining which channel code that was used on a communication link. In the proposed scheme, the receiver does not need to receive the entire data to determine the actual code. Moreover, the proposed scheme can also be used to determine the interleaving/scrambling sequence that was used at the transmitter. We investigate the performance of the scheme for some standard convolutional codes., ©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Reza Moosavi and Erik G. Larsson, A Fast Scheme for Blind Identification of Channel Codes, 2011, accepted The 54th IEEE Global Communications Conference (GLOBECOM).

We present a fast mechanism for determining which channel code that was used on a communication link. In the proposed scheme, the receiver does not need to receive the entire data to determine the actual code. Moreover, the proposed scheme can also be used to determine the interleaving/scrambling sequence that was used at the transmitter. We investigate the performance of the scheme for some standard convolutional codes., ©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Reza Moosavi and Erik G. Larsson, A Fast Scheme for Blind Identification of Channel Codes, 2011, accepted The 54th IEEE Global Communications Conference (GLOBECOM).

We present a fast mechanism for determining which channel code that was used on a communication link. In the proposed scheme, the receiver does not need to receive the entire data to determine the actual code. Moreover, the proposed scheme can also be used to determine the interleaving/scrambling sequence that was used at the transmitter. We investigate the performance of the scheme for some standard convolutional codes., ©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Reza Moosavi and Erik G. Larsson, A Fast Scheme for Blind Identification of Channel Codes, 2011, accepted The 54th IEEE Global Communications Conference (GLOBECOM).

A multiplicity of autonomous terminals simultaneously transmits data streams to a compact array of antennas. The array uses imperfect channel-state information derived from transmitted pilots to extract the individual data streams. The power radiated by the terminals can be made inversely proportional to the square-root of the number of base station antennas with no reduction in performance. In contrast if perfect channel-state information were available the power could be made inversely proportional to the number of antennas. A maximum-ratio combining receiver normally performs worse than a zero-forcing receiver. However as power levels are reduced, the cross-talk introduced by the inferior maximum-ratio receiver eventually falls below the noise level and this simple receiver becomes a viable option.

We derive detection metrics for soft-output diversity combining for the case of imperfect channel state information at the receiver. We treat in particular the case when the noise variance at the receiver is unknown. We contrast conventional training-based methods to a detector based on the generalized likelihood-ratio (GLR) test paradigm. We study the performance of the detectors via EXIT chart analysis and via simulations of LDPC coded transmission over a fast Rayleigh fading channel. The results show that the GLR receivers can significantly outperform the conventional detectors., ©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.Erik G. Larsson, Ragnar Thobaben and Gang Wang, On Diversity Combining with Unknown Channel State Information and Unknown Noise Variance, 2010, Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC).http://dx.doi.org/10.1109/WCNC.2010.5506707

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 the 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 and a greedy algorithm to approximate it in a computationally feasible fashion.

We study the NP-hard problem of scheduling andpower control with quality-of-service (QoS) constraints. We consider a generic wireless network comprising K mutually interfering links and N < K orthogonal time or frequency slots. We formulate the joint resource allocation problem as a constrained optimization problem, specifically, as a mixed integer programming (MIP) problem. This enables us to solve the problem exactly, and relatively efficiently for the vast majority of instances, using off-the-shelf algorithms. We also apply our formulation to the paradigm of cognitive underlay networks., Eleftherios Karipidis, Erik G. Larsson and Kaj Holmberg, Optimal Scheduling and QoS Power Control for Cognitive Underlay Networks, 2009, Proceedings of the 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP'09), 408-411.http://dx.doi.org/10.1109/CAMSAP.2009.5413245

In a multi-user MIMO downlink where the base station has only estimates of the channels of the users, the sum-rate of multi-user beamforming saturates at high SNR. However, this is not the case for single-user beamforming. We propose a low-complexity user scheduling algorithm that selects the number of active users based on a closed-form approximation of the average sum-rate, and in particular does not add multiple users in the single-user optimality range. In order to develop this algorithm we derive the expected value of the rate of zero-forcing beamforming and MMSE beamforming with estimated channels and modify the greedy user selection accordingly. The gain of the proposed method is shown in numerical simulations.

Recently, it was shown that the rates at the non-cooperative Nash equilibrium (NE) strategy are poor especially in the medium and high SNR regimes. A reasonable outcome of the cooperative approach, close to the Pareto boundary of the achievable rate region, was shown to be the zero-forcing (ZF) strategy. In this work, we prove that any point on the Pareto boundary can be achieved by a certain linear combination of the NE and ZF strategies. A scalar weight per user chooses between "selfish" (NE) and altruistic (ZF) behavior. Thereby, the difficult beamforming optimization is reduced to a simple weight optimization. Different optimal operating points, e.g. maximum weighted sum-rate, the Nash-bargaining solution, or the Egalitarian solution, can be obtained by a computationally efficient iterative algorithm. The results are characterized by instantaneous achievable rate regions and the corresponding operating points.