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59
Dirtypaper coding versus TDMA for MIMO broadcast channels
 IEEE Trans. Inf. Theory
, 2005
"... Abstract—We compare the capacity of dirtypaper coding (DPC)to that of timedivision multiple access (TDMA)for a multipleantenna (multipleinput multipleoutput (MIMO)) Gaussian broadcast channel (BC). We find that the sumrate capacity (achievable using DPC)of the multipleantenna BC is at most ��� ..."
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Cited by 66 (3 self)
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Abstract—We compare the capacity of dirtypaper coding (DPC)to that of timedivision multiple access (TDMA)for a multipleantenna (multipleinput multipleoutput (MIMO)) Gaussian broadcast channel (BC). We find that the sumrate capacity (achievable using DPC)of the multipleantenna BC is at most ��� @ A times the largest singleuser capacity (i.e., the TDMA sumrate)in the system, where is the number of transmit antennas and is the number of receivers. This result is independent of the number of receive antennas and the channel gain matrix, and is valid at all signaltonoise ratios (SNRs). We investigate the tightness of this bound in a timevarying channel (assuming perfect channel knowledge at receivers and transmitters)where the channel experiences uncorrelated Rayleigh fading and in some situations we find that the dirty paper gain is upperbounded by the ratio of transmittoreceive antennas. We also show that ��� @ A upperbounds the sumrate gain of successive decoding over TDMA for the uplink channel, where is the number of receive antennas at the base station and is the number of transmitters. Index Terms—Broadcast channel (BC), channel capacity, dirtypaper coding (DPC), multipleinput multipleoutput (MIMO) systems, timedivision multiple access (TDMA). I.
From Single user to Multiuser Communications: Shifting the MIMO paradigm
 IEEE Sig. Proc. Magazine
, 2007
"... In multiuser MIMO networks, the spatial degrees of freedom offered by multiple antennas can be advantageously exploited to enhance the system capacity, by scheduling multiple users to simultaneously share the spatial channel. This entails a fundamental paradigm shift from single user communications, ..."
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Cited by 44 (12 self)
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In multiuser MIMO networks, the spatial degrees of freedom offered by multiple antennas can be advantageously exploited to enhance the system capacity, by scheduling multiple users to simultaneously share the spatial channel. This entails a fundamental paradigm shift from single user communications, since multiuser systems can experience substantial benefit from channel state information at the transmitter and, at the same time, require more complex scheduling strategies and transceiver methodologies. This paper reviews multiuser MIMO communication from an algorithmic perspective, discussing performance gains, tradeoffs, and practical considerations. Several approaches including nonlinear and linear channelaware precoding are reviewed, along with more practical limited feedback schemes that require only partial channel state information. The interaction between precoding and scheduling is discussed. Several promising strategies for limited multiuser feedback design are looked at, some of which are inspired from the single user MIMO precoding scenario while others are fully specific to the multiuser setting. 1 DRAFT
Linear precoding in cooperative MIMO cellular networks with limited coordination clusters
 IEEE J. Sel. Areas Commun
, 2010
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On the user selection in MIMO broadcast channels
 IN PROC. OF INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY
, 2005
"... In this paper, a downlink communication system, in which a Base Station (BS) equipped with M antennas communicates with N users each equipped with K receive antennas, is considered. An efficient suboptimum algorithm is proposed for selecting a set of users in order to maximize the sumrate throughpu ..."
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Cited by 34 (5 self)
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In this paper, a downlink communication system, in which a Base Station (BS) equipped with M antennas communicates with N users each equipped with K receive antennas, is considered. An efficient suboptimum algorithm is proposed for selecting a set of users in order to maximize the sumrate throughput of the system. For the asymptotic case when N tends to infinity, the necessary and sufficient conditions in order to achieve the maximum sumrate throughput, such that the difference between the achievable sumrate and the maximum value approaches zero, is derived. The complexity of our algorithm is investigated in terms of the required amount of feedback from the users to the base station, as well as the number of searches required for selecting the users. It is shown that the proposed method is capable of achieving a large portion of the sumrate capacity, with a very low complexity.
Transmit selection diversity for unitary precoded multiuser spatial multiplexing systems with linear receivers
 IEEE TRANS. ON SIGNAL PROCESSING
, 2007
"... Multiuser spatial multiplexing is a downlink transmission technique that uses linear transmit precoding to multiplex multiple users and precancel interuser interference. In such a system the spatial degrees of freedom are used for interference mitigation and generally come at the expense of diver ..."
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Cited by 18 (6 self)
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Multiuser spatial multiplexing is a downlink transmission technique that uses linear transmit precoding to multiplex multiple users and precancel interuser interference. In such a system the spatial degrees of freedom are used for interference mitigation and generally come at the expense of diversity gain. This paper proposes two precoding methods that use extra transmit antennas, beyond the minimum required, to provide additional degrees of diversity. The approach taken is to solve for a unitary transmit precoder, under a zero interuser interference constraint, that minimizes an upper bound on the symbol error rate (SER) for each user. Solutions where all transmit antennas are employed as well as subsets of antennas (to reduce analog components) are described. Numerical results confirm a dramatic improvement in terms of SER and mutual information over single user MIMO methods and static allocation methods. For example, the proposed techniques achieve an SNR improvement of 610 dB at an uncoded SER of 10 −3, with only one extra transmit antenna.
Delay considerations for opportunistic scheduling in broadcast fading channels
 IEEE Trans. Wireless Commun
, 2007
"... We consider a singleantenna broadcast block fading channel with users where the transmission is packetbased. We define the (packet) delay as the minimum number of channel uses that guarantees all users successfully receive packets. This is a more stringent notion of delay than average delay and is ..."
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Cited by 13 (1 self)
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We consider a singleantenna broadcast block fading channel with users where the transmission is packetbased. We define the (packet) delay as the minimum number of channel uses that guarantees all users successfully receive packets. This is a more stringent notion of delay than average delay and is the worst case (access) delay among the users. A delay optimal scheduling scheme, such as roundrobin, achieves the delay of. For the opportunistic scheduling (which is throughput optimal) where the transmitter sends the packet to the user with the best channel conditions at each channel use, we derive the mean and variance of the delay for any and. For large and in a homogeneous network, it is proved that the expected delay in receiving one packet by all the receivers scales as, as opposed to for the roundrobin scheduling. We also show that when grows faster than, for some, then the delay scales as. This roughly determines the timescale required for the system to behave fairly in a homogeneous network. We then propose a scheme to significantly reduce the delay at the expense of a small throughput hit. We further look into the advantage of multiple transmit antennas on the delay. For a system with antennas in the transmitter where at each channel use packets are sent to different users, we obtain the expected delay in receiving one packet by all the users. Index terms: broadcast channel, fading, opportunistic scheduling, packet delay, longest queue. 1
Enhancing coverage and capacity for multiuser MIMO systems by utilizing scheduling
 IEEE Trans. on Wireless Commun
, 2006
"... Abstract — Recent studies have revealed that the remarkable capacity improvement resulting from an openloop multipleinputmultipleoutput (MIMO) spatial multiplexing system may come at the sacrifice of degrading link reliability. This tradeoff between antenna multiplexing gain against antenna diver ..."
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Cited by 10 (1 self)
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Abstract — Recent studies have revealed that the remarkable capacity improvement resulting from an openloop multipleinputmultipleoutput (MIMO) spatial multiplexing system may come at the sacrifice of degrading link reliability. This tradeoff between antenna multiplexing gain against antenna diversity gain may translate into smaller coverage areas. In this paper, we suggest using the multiuser diversity to replenish the diversitydeficient spatial multiplexing MIMO system. Specifically, we propose a fair scheduling scheme, called the strongestweakestnormalizedsubchannelfirst (SWNSF) scheduling, which requires only limited amount of feedback. Our analysis and results indicate that the SWNSF scheduling can significantly increase the coverage of the multiuser MIMO system while further improving the system capacity.
Capacity of linear multiuser MIMO precoding schemes with measured channel
 data,"9th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2008
"... In multiuser multipleinput multipleoutput (MUMIMO) systems, spatial multiplexing can be employed to increase the throughput without the need for multiple antennas and expensive signal processing at the user equipments. In theory, MUMIMO is also more immune to most of propagation limitations pla ..."
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Cited by 8 (5 self)
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In multiuser multipleinput multipleoutput (MUMIMO) systems, spatial multiplexing can be employed to increase the throughput without the need for multiple antennas and expensive signal processing at the user equipments. In theory, MUMIMO is also more immune to most of propagation limitations plaguing singleuser MIMO (SUMIMO) systems, such as channel rank loss or antenna correlation. In this paper we compare the performance of different linear MUMIMO precoding schemes using real channel measurement data. The measurement data has been acquired using Eurecom’s MIMO Openair Sounder (EMOS). The EMOS can perform realtime MIMO channel measurements synchronously over multiple users. The results show that MUMIMO provides a higher throughput than SUMIMO also in the measured channels. However, the throughput in the measured channels is by far worse than the one in channels without spatial correlation. Of all the evaluated linear precoding schemes, the MMSE precoder performs best in the measured channels. 1.
Opportunistic feedback protocol for achieving sumcapacity of the MIMO broadcast channel
 in proceedings of IEEE VTC Fall
, 2007
"... Abstract — We consider a feedback protocol with a limited amount of feedback that achieves the asymptotic sumrate capacity. Time slots for channel feedback correspond not to users, but to a channel value; thus, users opportunistically access these slots based on their channel state information (CSI ..."
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Cited by 7 (3 self)
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Abstract — We consider a feedback protocol with a limited amount of feedback that achieves the asymptotic sumrate capacity. Time slots for channel feedback correspond not to users, but to a channel value; thus, users opportunistically access these slots based on their channel state information (CSI) measurement. We show analytically that the proposed SF protocol a) requires finite number of feedback slots upper bounded by a small number, b) is fully distributed, c) needs finite transmission energy during feedback and d) asymptotically achieves the sumcapacity of the MIMO BC. Numerical results show that the proposed feedback protocol performs close to a system with perfect CSI at the transmitter, with substantially less number of feedback bits compared with conventional CSI feedback methods because feedback requirements only grow as log 2 (K) rather than linearly with K, where K is the number of users. I.
A delay analysis for opportunistic transmission in fading broadcast channel,” ro be submitted io IEEE Tmns. Info. { d o w n h d muiiable at wivw.its.calteci~ e d d  m o d
, 2004
"... Abstract We consider a singleantenna broadcast block fading channel (downlink scheduling) with TL users where the transmission is packetbased and all users are backlogged. We define the delay as the minimum number of channel uses that guarantees ull n users successfully receive m packets. This i ..."
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Cited by 7 (2 self)
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Abstract We consider a singleantenna broadcast block fading channel (downlink scheduling) with TL users where the transmission is packetbased and all users are backlogged. We define the delay as the minimum number of channel uses that guarantees ull n users successfully receive m packets. This is a more stringent notion o f delay than average delay and is the worst case delay among the users. A delay optimal scheduling scheme, such as roundrobin, achieves the delay of mn. In a heterogeneous network and for the optimal throughput strategy where the transmitter sends the packet to the wet with the best channel conditions, we derive the moment generating function of the delay for any m and n. For large n and in a homogeneous network, the expected delay in receiving one packet by all the receivers scales as n log n, as opposed to n for the roundtobin scheduling. We also show that when m grows faster than (logn)‘, for some P> 1, then the expected value of delay scales like mn, This roughly determines the timescale required for the system to behave fairly in a homogeneous network. We then propose a scheme to signikantly reduce the delay at the expense of a small throughput hit. We further look into two generalizations of our work: i) the effect of temporal channel correlation and i i) the advantage of multiple transmit antennas on the delay. For a channel with memory of two, we prove that the delay scales again like n log n no matter how severe the correlation is. For a system with A4 transmit antennas, we prove that the expected deky in receiving one packet by all the users scales like nf+”dF$,,, for large n and when M is not growing faster than logn. Thus, when the temporal channel correlation is zero, multiple transmit antenna systems do not reduce the delay significantly. However, when channel correlation is present, they can lead to significant gains by “decorrehting ” the effective channel through means such as random beamforming.